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The effects of International Financial Reporting Standards (IFRS) adoption on
audit fees in Ethiopia - The case of commercial banks
By: Amanuel Tsegaye
Thesis submitted to the Addis Ababa University Department of Accounting and
Finance in partial fulfillment of the requirements for the degree of Master of
Science in Accounting and Finance
Advisor: Dr. Temesgen Worku
January, 2019
Addis Ababa, Ethiopia
ADDIS ABABA UNIVERSITY
SCHOOL OF GRADUATE STUDIES
I
Addis Ababa University
School of Graduate Studies
This is to certify that the thesis prepared by Amanuel Tsegaye, entitled: The effects of
international financial reporting standards (IFRS) adoption on Audit fees in Ethiopia- The case
of commercial banks in in partial fulfillment of the requirements for the degree of Master of
Science in Accounting and Finance complies with the regulations of the University and meets
the accepted standards with respect to originality and quality.
Approved by:
Approved by a board of Examiners and Advisor:
__________________________________________________________________
Chair of Department or Graduate Program Coordinator
Dr.
internal Examiner
______________
Signature
______________
Date
Dr.
External Examiner
______________
Signature
______________
Date
Dr. Temesgen Worku
Advisor
______________
Signature
______________
Date
II
Table of Contents
List of Tables and Figures ...................................................................................................................... V
Declaration ............................................................................................................................................ VI
ABSTRACT ........................................................................................................................................ VII
Acknowledgements ............................................................................................................................ VIII
Acronyms .............................................................................................................................................. IX
CHAPTER ONE ..................................................................................................................................... 1
INTRODUCTION .................................................................................................................................. 1
1.1 Background of the Study......................................................................................................... 1
1.2 Statement of the Problem ........................................................................................................ 5
1.3 OBJECTIVES OF THE STUDY ............................................................................................ 9
1.3.A General objective ............................................................................................................ 9
1.3.B Specific objectives .......................................................................................................... 9
1.4 Research Questions ............................................................................................................... 10
1.5 Research Hypotheses ............................................................................................................ 10
1.6 Significance of the Study ...................................................................................................... 10
1.7 Limitation of the Study ......................................................................................................... 12
CHAPTER TWO .................................................................................................................................. 13
LITERATURE REVIEW ..................................................................................................................... 13
2.1 International Financial Reporting Standard .......................................................................... 13
2.1.1 General Overview of IFRS ........................................................................................... 13
2.1.2 IFRS in Ethiopia............................................................................................................ 14
2.1.2.1 Enactment of the Financial Reporting Proclamation ........................................................ 16
2.1.2.2 Establishment of the Board ............................................................................................... 17
2.1.2.3 Roadmap to IFRS Implementation in Ethiopia ................................................................. 18
2.2 Audit Fee Formation ............................................................................................................. 19
2.3 The audit fee Model .............................................................................................................. 20
2.4 Empirical Review .................................................................................................................. 23
2.4.1 Variables ....................................................................................................................... 26
CHAPTER THREE ............................................................................................................................ 35
METHODOLOGY ............................................................................................................................. 35
3.1 Overview ............................................................................................................................... 35
3.2 The Research Design ............................................................................................................ 35
3.3 SAMPLING Design .............................................................................................................. 36
III
3.3.1 The Target Population ................................................................................................... 36
3.3.2 Sampling Technique ..................................................................................................... 37
3.3.3 Sample Size ................................................................................................................... 37
3.4 Study Period .......................................................................................................................... 38
3.5 Data Collection Procedures and Data Source ....................................................................... 39
3.5.1 Data Collection Procedures ........................................................................................... 39
3.5.2 Data Source ................................................................................................................... 39
3.5.3 Population Inclusion Criteria ........................................................................................ 39
3.6 Research Model .................................................................................................................... 40
3.6.1 Specifications of Model Variables ................................................................................ 41
3.6.2 Models for total fees paid to the statutory auditor ........................................................ 41
3.6.3 Audit Fees ..................................................................................................................... 42
3.6.4 IFRS .............................................................................................................................. 42
3.6.5 The Size of an Audit Client Company .......................................................................... 43
3.6.6 Audit Complexity .......................................................................................................... 44
3.6.7 Risk ............................................................................................................................... 45
3.6.8 Auditor Type ................................................................................................................. 47
3.7 Empirical Estimation Models ................................................................................................ 48
3.8 Method of Data Analysis ...................................................................................................... 48
3.8.1 Resolving Data Analysis Assumptions ......................................................................... 49
CHAPTER FOUR ............................................................................................................................... 55
DATA ANALYSIS AND PRESENTATION .................................................................................... 55
4.1 Introduction ........................................................................................................................... 55
4.2 Descriptive Analysis ............................................................................................................. 55
4.2.1 Descriptive Analysis on Audit fees ............................................................................... 55
4.2.2 Annual Audit Fee Statistics ........................................................................................... 56
4.3 Pre-Post IFRS Variance Analysis of AF ............................................................................... 60
4.4 The Correlation Analysis for Audit Fee Model .................................................................... 60
4.5 The Multivariate Regression Analysis .................................................................................. 62
4.5.1 Random Effect Model Analysis of Audit Fee ............................................................... 62
4.5.2 Regression Results for Audit Fee Model ...................................................................... 63
4.5.3 Further Analysis: Audit Fee Model............................................................................... 65
CHAPTER FIVE ................................................................................................................................ 68
DISCUSSION, RECOMMENDATION AND CONCLUSION ...................................................... 68
IV
5.1 Summary of Findings ............................................................................................................ 68
5.2 Discussion ............................................................................................................................. 68
5.3 Conclusion ............................................................................................................................ 71
5.4 Recommendation .................................................................................................................. 71
5.4.1 Contribution of the Study .............................................................................................. 71
5.4.2 Future Research Considerations .................................................................................... 71
REFERENCES ..................................................................................................................................... 72
APPENDIXES ...................................................................................................................................... 83
V
List of Tables and Figures
Table-1: Multicollinearity Analysis Statistics ____________________________________ 50
Table 2: Hausman’s Specification Test _________________________________________ 53
Table 3: Variables Summary Statistics __________________________________________ 55
Table 5: t-test AF Means based on IFRS ________________________________________ 60
Table 6: Correlation Matrix for the Variables in the Audit Fee Model _________________ 61
Table 7: Random-Effects Regression Results _____________________________________ 63
Table 8: Random effect regression analysis of significant variables ___________________ 66
VI
Declaration
I, Amanuel Tsegaye declare that this paper is a result of my independent research work on the
topic entitled the effects of international financial reporting standards (IFRS) adoption on Audit
fees in Ethiopia- the case of commercial banks in partial fulfillment of the requirements for the
degree of masters of science in Accounting and Finance at Addis Ababa University. This work
has not been submitted for a degree to any other academic entity. All the references are also
duly acknowledged.
Amanuel Tsegaye
Signature:_________________
Date: ____________________
VII
ABSTRACT
The objective of this study is to assess the effects of mandatory adoption of IFRS on the audit
fees of Commercial Banks (CB) in Ethiopia and it utilized correlational research design with
quantitative data collection and analysis on the data gathered from yearly financial audit
reports of the banks during the period of 2014 to 2018. Despite population of the study is
limited to existing CBs, the study employed purposive sampling technique in the selection of
the banks (n = 17) to comply with availability and accessibility of data that excluded the CBE
(the only governmental bank) due to lack of complete data. The data has been analyzed with
descriptive, independent t-test, correlation and panel regression analysis statistical techniques
using STATA and SPSS software packages. Findings of the study showed a significant positive
relationship between IFRS and audit fees which shows that IFRS adoption substantially
increased audit fees among commercial banks operating in Ethiopia. This is attributed to the
general complexity of the IFRS adoption in Ethiopia. The study also finds that banks audited
by the Non-GradeA audit firms experience greater audit fee increase in post IFRS period than
those audited by the GradeA audit firms. However, the study is limited to the Commercial
Banks in Ethiopia, thus, future studies that include several industries might provide better
understanding of the influence of IFRS adoption on audit fees.
KEY WORDS:
IFRS Adoption; Audit fees; Regulatory reforms; Commercial banks of Ethiopia
VIII
Acknowledgements
Firstly, I am grateful for his gracious God not only for giving me the courage and persistence
accomplish this paper rather for his endlessness love and countless mercy.
I would like to express my deepest gratitude to my Advisor Dr. Temesgen Worku for his
dedication, advices and technical supports to prepare this research. I would also like to broaden
my thanks to Addis Ababa University College of Business and Economics for giving me the
chance to conduct this research paper and to continue my education for MSc degree in
Accounting and Finance.
My sincere and deepest gratitude goes to my life-coach, Mama Menna for your moral and
spiritual support. Mom your unshakable confidence and love, whatsoever the situation I am in,
helped me to stay sane and focused in my study. My grateful thanks also go to my Dad Eng.
Tsegaye Ghershen for your aspiring guidance, invaluably constructive advices. I am also
grateful to my beloved family Zion Fasik Rich and Awi for your moral support along the way,
your belief in me and understanding when I am down always keeps me back in the track.
Throughout the course of conducting this research, I would be remiss if I did not mention my
best friends, Fike Mess Tomi and Sami in sharing helpful ideas and resources. All those friends
of mine who may feel to be acknowledged here, but I failed to do so, because of lenient nature
of mine, I shall owe my deepest gratitude as well.
IX
Acronyms
AABE Accounting and auditing Board of Ethiopia
ACCA Association of Chartered and Certified accountants
ECXA Ethiopia Commodity Exchange Authority
ECX Ethiopia Commodity Exchange
EPAAA Ethiopian Professional Association of Accountants an
FASB Financial Accounting Standards Board
GAAP General Accepted Accounting Principles
IAS International Accounting Standards
IASB International Accounting Standards Board
IASC International Accounting Standards Committee
IFAC International Federation of Accountants
IFRS International Financial Reporting Standards
ROSC Report on the Observance of Standards and Codes
SME Small and Medium Enterprise
SPSS Statistical package for social science
1
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
The increasing growth in international trade and investment has brought to the fore the
enthusiasm for adoption of International Financial Reporting Standards (IFRS) by both the
developed and developing countries (Owolabi & Iyoha, 2012). In the past few years, many
developed and developing countries have adopted IFRS as the basis for financial reporting
(Thompson 2016). Companies, who operate in a demanding market, whose competition grows
in fiercer way, the accounting information stands as a strategically able to provide cross border
expansion opportunities, as investors are able to assess the legislations of different companies
in different countries. Reliable financial records are vital for the very survival of the
contemporary social order. The accounting and auditing processes have come under sharp
scrutiny in the wake of Enron and other financial scandals. High quality, comprehensive
reporting standards followed by attestation of qualified independent auditors play a vital role
in enhancing the reliability of financial information and veracity of the financial statements.
High quality accounting and financial reporting aids the public to apportion their hard-earned
resources efficiently. When making decisions about capital allocation, investors need to know
that financial information they are given is credible and reliable. Eminent financial reporting
framework, enhanced accounting standard, quality audits and audit opinions on financial
reports are crucial to achieving investor confidence. (Rajgopal, Suraj & Zheng, 2015).
Proponents of IFRS claim that IFRS will improve quality of financial reports, improve the
comparability of entities, it gives better access to global capital markets, reduced cost of capital,
2
and encourages cross border fund acquisitions (Ball, 2006). Despite its advantages, IFRS
adoption also consumes additional costs in capacity building programs and implementation
processes by all regulatory bodies, firms and training institutions in order to provide the needed
manpower for IFRS implementation, monitoring and compliance. As such, many developing
countries are currently migrating to IFRS by abandoning their national accounting
standards. Adopting IFRS as a national standard will have significant benefits for companies
to improve corporate transparency that is required by investors and the public (E. Dodzi, 2015).
In recognition of the adoption, Ethiopian government officially declared the adoption of IFRS
by the issued Proclamation No.847/2014 “Financial Report Proclamation of Ethiopia” which
entail Ethiopian companies to follow IFRS in their financial statement presentation. (Federal
Negarit Gazeta, 2014). According to Fantahun (2012), previous Ethiopia's financial reporting
practices were driven by its tax laws and fragmented accounting practices acquired from the
country's institutions of higher learning. He further claims that IFRS helps to acquire
nationwide conceptual framework to guide selection and application of an accounting
principle, realization of reliable and comparable financial information. The pre-IFRS financial
reporting system is erratic because decision to select and apply measurement and disclosure of
financial transactions were left to the company's management and its auditors (Fantahun,
2012).
Fantahun (2012) further argues that it will be extra beneficial for countries like Ethiopia, which
had no clear accounting regulation except the 1960’s set of rules and tax laws which requires
a list of detailed rules to be followed in financial statement reporting. Moreover, after the
adoption of the IFRS, the Ethiopian accounting environment witnessed and still present several
changes that affect especially, the financial statements prepared by companies (Fareedmastan,
Gebru, Anuradha & Fissa, 2015).
3
De-Fuentes and Sierra-Grau (2015) examined business enterprises from 21 countries that
voluntarily adopted IFRS between 1994 and 2003 and provided evidence that there was an
improvement in the quality of the information covered in the financial statements associated
with the application of IFRS. The application of this standard have brought significant benefits
to most companies such as improving the comparability of financial information (Fantahun,
2012; Kamwenji, 2014), lower cost of capital (Outa, 2011), increase transparency and quality
of financial reports (Vieru, Markku & Hannu, 2010; Yaacob & Che-Ahmad, 2012), positive
effect on the capital market (Jacob & Madu, 2009; Kim, Liu, & Zheng, 2012; Shan & Troshani,
2016) predicted by analysts (Humphrey, Loft, & Woods, 2009; Okpala, 2012). Subsequent
studies analyzing the effect of mandatory adoption of IFRS on the quality of accounting
information in the European Union have yielded similar results (Chen, 2017; Gellings, 2017;
Jacob & Madu, 2009; Lin & Yen, 2016; Lourenço & Branco, 2015),
Accordingly, studies in Ethiopian context affirm that adopting IFRS have improved the
qualitative characteristics of accounting information, such as comprehensibility, relevance,
reliability, comparability, providing a better quality of information. (Fantahun, 2012; Simegn,
2015; Alemi, 2016; Teshome, 2017)
However, there is an edgy argument by opponents of IFRS in the field claiming that the
mandatory adoption of IFRS is associated with significant implementation cost that can reduce
alleged benefits. They further claim that out of this implementation cost; audit fee takes the
lion share (De George et al., 2013). The adoption of IFRS is usually associated with an
increased complexity of recognition, measurement and disclosure of elements in the financial
statements and requires a greater judgment of preparers, and a more careful work of those who
audit the information disclosed (Mulley et al., 2010). Because IFRSs are principle based
accounting standards, there is no specific rule as to the accounting treatment, therefore, due to
4
the lack of clear accounting treatments to follow; it requires more time and efforts to the
accountants and auditors to asses’ proper accounting treatment for the corporate transactions
(Vrentzou, 2011).
Therefore, the adoption of principle based IFRS, unarguably intensifies the complexity of the
reporting environment, giving rise to increase in audit fees due to the increase in effort and
time required to audit the detailed and complex requirements of IFRS. Moreover, studies on
IFRS consequences revealed that the IFRS adoption process as costly, complex and
burdensome. (Glover, Taylor & Wu, 2017; Jermakowicz & Gornik-Tomaszewski, 2006; Vieru
et al., 2010). Complex nature of IFRS and problems related to the lack of proper
implementation makes IFRS more challenging. (Jermakowicz & Gornik-Tomaszewski, 2006).
The move towards a global accounting standard therefore, increases clients accounting and
reporting complexity and client’s potential insufficient preparations can result in risks in their
audit assignment, Furthermore, the increased accounting regulation will cause extra client risk
and more time consuming work for the auditor, these complexities, audit risk in turn, are likely
to be reflected in audit and non-audit fees (Vieru et al., 2010). Therefore, as the objective of
the current study is investigate effects of IFRSs adoption on Audit fees in Ethiopia - in the case
of commercial banks, the study also addresses associated factors such as Size of the audit firms,
grade of the auditor, financial risks and audit complexity that might influence the audit fees
after adoption of IFRSs.
5
1.2 Statement of the Problem
Comparison of the information present in the financial statements of companies from different
countries was usually a complex task. The various types of legal systems combined with other
countries' economic and political differences have supported a wide range of accounting
systems (Lourenço & Branco, 2015; Ochei & Akande, 2012).
Globalized financial accounting and standardized reports have become artefacts capable of
increasing comparability between companies located in different countries, contributing to
efficiency in conducting business across borders by conducting international business and
attracting external resources (Herbert & Tsegba, 2013). Madawaki, (2012) argues that
international accounting standards (IFRS) represent a set of standards that are constantly
updated with the current requirements of the world market, and are therefore accepted in a
gradual way in several countries.
In December 28, 2014 the Ethiopian government enacted, the Financial Reporting
Proclamation, Proc No. 847/2014. This proclamation led to changes in most/ all accounting
aspects in Ethiopia. According to Addis fortune reporter Samson Birhane, “many are hopeful
that it will have a positive impact on the external auditing market”. The newspaper further
discussed the merits of IFRS, noted the views of practitioners, scholars and stakeholders, one
of the interviewee, Abdulmenan Mohammed, an expert with 15 years of auditing experience
in England and Ethiopia said “It is a cure for the riddled auditing profession with sub-standard
works, unaccountable practices and race-to-the-bottom price competitions," (Fortune, 2017)
The introduction of any new accounting framework affects all facets of reporting (Konadu,
2018). While IFRS proponents, supporters, and regulators have joined the acclaimed adoption
benefits to improve the quality and credibility of financial information, promote global
6
comparability and increase investor confidence, implementation of these new standards come
with significant cost implications and one major aspect of the transitional cost is an increase in
audit function (ICAEW, 2007).
The enormous rapidity of IFRS adoption worldwide have been documented as the biggest
change in accounting standards ever seen, and represents another opportunity to examine the
effect of regulatory changes on the external audit function. According to Kim et al. (2012), the
economic implications of the adoption of IFRS have attracted the interests of stakeholders, and
the parties interested in the accounting profession. academic literature have paid considerable
attention to the assessment of their economic relevance since the application of mandatory
adoption of IFRS between companies listed on the stock exchanges of EU countries. Since then
many studies have been conducted to examine the net benefit of IFRS, and documented a sharp
rise in audit fees, attributable primarily to the increased audit effort and audit risk resulting
from the increased complexity of recognition, measurement and disclosure of elements in the
financial statements (Kim et al., 2012).
At the international level, there is evidence that the application of IFRS is associated with an
increase in the complexity of the audit and, consequently, the fees charged by the auditors. A
survey of Institute of Chartered Accountants in England and Wales (ICAEW, 2007) reported
that 67 percent of auditors in European Union (EU) stated that the audit fees have increased
after IFRS implementation in financial statement. The ICAEW survey report revealed that the
major IFRS related costs is still the escalation of audit fees.
According to Fantahun (2012), one of the basic features of IFRS is that it is a principle based
standard and seeks to avoid a rule based mentality. The IASB framework establishes a general
requirement to account for transactions in accordance with their substance, rather than only
7
their legal form. Indeed, IFRS is a complex standard and involves comprehensive detailed
disclosures than most previous local GAAPs, as a result it demands greater effort from auditors
to conduct the audit assignment. moreover, IFRS inspires transparent reporting, which again
call for difficult estimations and higher professional judgment from auditors than most previous
local GAAPs that are based on rules and historical cost assumptions (Kim, Yang & Boulevard,
2012). Thus the application of IFRS not only requires exercise of higher level of judgment by
the preparer, but a more careful work of those who audit the disclosed information.
Numerous academic studies have explored the impact of regulatory changes on audit fees and
found mixed results. Griffin, Lont and Sun, (2009) reported that the mandatory adoption of
IFRS considerably increased audit fees charged to New Zealand companies; Vieru et al., (2010)
found similar result by Finland companies. Moreover, Kim et al. (2012) in Europe and De-
George, Ferguson & Spear, (2013) in Australia have provided consistent evidence of an
increase in audit fees after the adoption of IFRS. Kim et al., (2012) found that the mandatory
adoption of IFRS provided an increase in audit costs on European companies, especially in
countries with lower levels of investor protection. De George et al. (2013) have evidenced an
association between the adoption of IFRS and an increase in audit fees in Australian companies,
especially in larger companies that require a more complex auditing process. Bratten, Gaynor,
McDaniel, Montague and Sierra (2013) found the adoption of IFRS to be more costly during
the year of transition as a result of the greater effort, knowledge, skill and competencies needed
to implement the new standard.
The adoption of IFRS is a major accounting event that increased the complexity of the audit
process, which increases the efforts required to undertake the audit and consequently translate
into high audit fees. Furthermore, Redmayne & Laswad (2013) argues that the augmented audit
8
fee is not merely, because auditors require more effort to go through all the detailed disclosure
but also more importantly, auditors demand more effort and time to reduce audit liabilities.
In African continent, Thompson (2016) in his article “Accounting for a Developing World: A
look at International Standards on Developing Countries”, reported evidence that the major cost
of the move towards IFRS by African countries is Audit and Audit related fees. According to
Thompson (2016), when a developing nation elects to adopt and implement IFRS, they often
face many challenges and hurdles along the way. He claim that choosing to implement
international accounting standards is simply the first step, and what follows is typically a long
line of issues that need to be resolved before the benefits, if any, are to be realized. Similarly
Konadu (2018) studied consequences of IFRS adoption based on 104 companies listed on the
stock exchanges in 8 African countries using publicly available data he concludes that in
agreement with Thompson (2016), audit fees have significantly increased as a result of
companies adopting IFRS. Moreover, Konadu (2018), claimed that the perceived benefits of
IFRS adoption have caused neglect in research on the possible unintended consequences of
IFRS on the audit market, specifically in Africa. Hence there is a need to empirically examine
the impact of IFRS adoption on the audit market in Africa.
Furthermore, Thompson (2016), claims that developing countries generally do not have an
established accounting and auditing tradition, lack a strong professional accounting body, the
accounting and auditing systems may be inadequate or nonexistent. Hence, the effect of
implementing International Financial Reporting Standards (IFRS) in developing countries
needs a detailed country specific study.
However, most of the studies conducted to date are in the context of developed economies with
established structures; the existence of such evidence in Ethiopia is not known yet. Prior
9
literature documented variation in the net benefits of IFRS adoption in different countries,
articulates the need to separate, and more fully understand, the costs associated with
harmonization” (De George et al., 2013). Hence this issue calls for the subjective evaluation of
the matter in Ethiopian context. This study therefore aims to examine the effect of the adoption
of IFRS on audit fee in Ethiopian context. This study further aim to contribute to the ongoing
debate on net benefit of IFRS adoption.
1.3 OBJECTIVES OF THE STUDY
1.3.A General objective
The main objective of this study was to assess the effects of adoption of International Financial
Reporting Standards (IFRS) on the audit fees in Ethiopia
1.3.B Specific objectives
To examine whether the mandatory adoption of IFRS affects the audit fee charged for
financial statement audit service.
To examine the level of audit fee variation for financial statement audit service prepared
under IFRS with similar statement prepared under previous GAAP counterpart.
To identify auditee related factor that affect the pricing of audit.
To examine whether the audit firm size affects the pricing of audit.
10
1.4 Research Questions
In view of the below research objectives, the following are the research question:
Q1: Does mandatory adoption of IFRS by Ethiopian companies have an impact on the audit
fees?
Q2: How the size & complexity of auditee affect the audit fees?
Q3: In what circumstances the size of audit firm affect the audit fees?
1.5 Research Hypotheses
Taking into consideration, the nature and extent of the problems stated so far, and prior
literatures discussed later, it is necessary to formulate the following hypotheses:
H1: There is a positive association between adoption of IFRS and audit fees.
H2: Given that the financial statements are prepared in accordance with IFRS, the extra audit
fees is higher for big and more complex firms than small firms.
H3: Audit fees is positively associated with the size of the audit firm after adoption of IFRS.
1.6 Significance of the Study
The significance of this study can also be seen in the line of research, practice and decision-
making. With respect to the relevance of research, much is not documented in Ethiopian context
in the existing literature either published research or journal article on how IFRS could affect
the audit of financial statements in Ethiopian setting, hence this study principally examine the
effects of the mandatory adoption of IFRS on the financial audits, specifically on audit fees,
using the Ethiopian banks as a subject matter.
11
Besides it contributes to, the edgy arguments by scholars in the field that the mandatory
adoption of IFRS is associated with significant implementation cost, out of which Audit fee is
forms the lion share (De George et al., 2013). This study helps to make an informed assessment
of the impact and suitability of the adoption of IFRS when evaluating its economic relevance.
Although Internationally, the variables of the research have been studied, as it is verified in the
works of (De George et al., 2012; Griffin et al., 2009; Kim et al., 2012; Lin & Yen, 2010; Vieru
et al., 2010). However, in the national level, the variables covered so far are inadequately
studied (Afesha, 2014; Mustafa, 2017).
The current study is one of the few studies that examine the impact of such major changes in
accounting, auditing and regulatory environment in Ethiopia. Besides, the fact that no empirical
evidence to date in the context of Ethiopia have showed the effects of the adoption of IFRS on
audit fees, this study will be forerunner to provide empirical evidence on the effects of the
adoption of IFRS on audit fees. Therefore, the current study might contribute to the scarce
theoretical knowledge regarding the variables that significantly affect the audit fee formation
in Ethiopian context as well as it might add up to the existing huge literature gap. With regards
to practical importance, the study might also be relevant for researchers, students and policy
makers in other developing countries who are yet to adopt the IFRS, in determining and
understanding the degree of complexity, the time it consumes and the monetary cost required
during implementation of IFRS and it might be an experience for predicting the opportunities
and challenges they encounter during adopting the Standards that their countries may.
12
1.7 Limitation of the Study
It is the wish of the researcher to study the effects of adoption of IFRS in audit function;
nevertheless, since the subject is very broad, all aspects of the issue couldn’t be assessed by
this thesis. Therefore, the study is limited to the specific effects of IFRS on audit fees. First,
the mandatory adoption of IFRS in Ethiopia mandated the financial sector and public entities,
to prepare their first IFRS based financial statements and results of their operation for the fiscal
year 2017/2018. This makes the population narrow therefore, the data constitutes relatively a
small sample size. To make the matter worse, there were circumstances in which incomplete
sets of financial information and records availed. Therefore, small population size and the
diminution in data due to the missing or incomplete annual reports would bring to the effect of
diminishing power of statistical tests applied. Hence, the statistical result may lead to inaccurate
indication on audit fees after IFRS adoption.
Secondly, the fact that this study used only financial institutions, comparisons between
industries and their relative complexities couldn’t be captured, added to this fact, number of
audit firms involved in the provision of audit service in this industry is limited, this may affect
pricing variability between the audit firms. Finally, In addition to the above-mentioned
limitations, the fact that no prior studies have been made in Ethiopia, in relation to the issue,
the model adopted and variables used in this study are selected based on prior literatures and
evidences in developed countries, though the study tried to contextualize to the Ethiopian
setting; it might not fully capture other country specific variables in Ethiopian context.
13
CHAPTER TWO
LITERATURE REVIEW
2.1 International Financial Reporting Standard
2.1.1 General Overview of IFRS
International Financial Reporting Standards are a single set of high quality, comprehensive
and enforceable global accounting standards that require transparent and comparable
information in general purpose financial statements issued by an independent organization
registered in US and operates in the United Kingdom known as the International Accounting
Standards Board (IASB). The move towards developing an acceptable global high quality
financial reporting standard started in 1973 when the International Accounting standards
committee (IASC) was formed by Professional Accounting Bodies from Canada, USA, United
Kingdom, Germany, France, Netherlands, Australia, Mexico and Japan (Iyoha, 2011). In
response to the globalization and growing demand for transparent, comparable financial
information in the markets in 2001, the International Accounting Standards Committee (IASC)
made a thorough restructure and formulated the International Accounting Standards Board
(IASB). The IASB, is responsible for issuing the International Financial Reporting Standards
(IFRS), These standards are issued after being developed through international due process
involving practitioner’s, accountants, financial analysts, the business community, stock
exchange regulators, legal authorities, and other interested organizations around the world
(Gina, Adeghe & Kingsley, 2016).The institution puts forward the standards that would better
serve public companies worldwide than the local standards in the country in regards to the
aspect of comparability, transparency and economic growth. The IASB besides issuing the
14
standards and interpretations, in pursuance of its objectives, the board cooperates with national
accounting standard setters to achieve convergence in accounting standards in the world (Gina,
Adeghe & Kingsley, 2016).
IASB claims to have a public commitment from 130 countries to its initiative of global
implementation of a single set of accounting standards. Of these, 116 countries require IFRS
for all or most of their domestic, publicly accountable entities whereas the remaining 14
countries allow or require IFRS for the publicly listed entities in their jurisdictions (IASB,
2016).
2.1.2 IFRS in Ethiopia
In Ethiopia, until recently, there was no legal requirement for compliance with any specific
accounting and auditing standards, except some directive and minor provisions issued in
various separate laws by various regulatory bodies.
Alemi and Pasricha, (2017) analyzed various legal documents pertaining to financial reporting
in Ethiopia. Their study revealed that corporate financial reporting legal and regulatory
frameworks are framed in Commercial Code of 1960, and disseminated between various
proclamations, regulations, directives, accounting procedures and manuals, codes of corporate
governance and has been regulated by different regulatory bodies as there has not been any
single organized financial reporting regulatory body in Ethiopia (Alemi & Pasricha, 2017).
Similarly, Reports on the Observance of Standards and Codes (ROSC Ethiopia, 2007), a joint
initiative by the World Bank and the International Monetary Fund (IMF) in consultation with
key stakeholders including governmental and non-governmental institutions conducted a
review of corporate sector accounting, auditing, and financial reporting practices and
15
supporting infrastructure in Ethiopia. The results of the review found that the Commercial Code
has made directors of companies responsible for preparation of financial statements, including
consolidated financial statements for group companies, and ensure an audit of the financial
statements conducted. Nonetheless, there is no requirement to comply with any accounting
standards while preparing financial statements, similarly, there is no requirement to comply
with any auditing standards in provisions for audit; furthermore, the report noted that the
qualification requirement of auditors to be nonexistent in the provisions (ROSC Ethiopia,
2007).
Furthermore, Alemi and Pasricha (2017) noted that even though the Office of the Federal
Auditor General (OFAG) was regulating the accountancy profession through the committee
established under its ambit but OFAG has had other broader responsibilities. As a result,
financial statements were not required to be filed and reviewed as to whether they have been
prepared in compliance with existing rules and regulation or not and the work of auditor has
not been reviewed (Alemi & Pasricha, 2017).
Based on its review ROSC-Ethiopia (2007) made the following recommendations: revise the
Commercial Code 1960 and other relevant laws and regulations; enact a financial reporting
law; establish a National Accountants and Auditors Board; set accounting standards and
mandate ISA for all auditors; establish a strong professional accountancy body with
membership of the International Federation of Accountants (IFAC); establish a local
professional and technician accountancy qualification; enhance the capacity of all regulators to
enable them to effectively discharge their responsibilities; and to handle International Financial
Reporting Standards-related issues in the regulation and conduct awareness campaigns and
related programs. In line with Recommendations of ROSC Ethiopia (2007), on December 5,
2014, the House of Representatives of Federal Democratic Republic of Ethiopia passed the
16
Financial Reporting Proclamation, proclamation No.847/2014. This proclamation pronounced
that Ethiopia officially adopted IFRS and mandated International Standards on Auditing (ISA)
for auditors. Moreover the ministry of council, though regulation no. 332/2014 established the
Accounting and Auditing Board of Ethiopia (AABE) to oversight such initiatives(Federal
Negarit Gazeta, 2014).
2.1.2.1 Enactment of the Financial Reporting Proclamation
The enactment of a Proclamation to Provide for Financial Reporting (Proclamation no.
847/2014) is the current development in the accounting, auditing and financial reporting history
in Ethiopia. The Ethiopian government as per the recommendation of (ROSC Ethiopia, 2007)
took a huge step in standardizing the financial accounting and auditing practices of the country.
The government of Ethiopia issued this proclamation to achieve the following objectives as
stated in Article 1 of the proclamation:
(A) To establish a sound, transparent and understandable financial reporting system
applicable to entities in both private and public sectors;
(B) To have a uniform financial reporting law that enhances transparency and
accountability by centralizing the hitherto decentralized financial reporting structures
of Ethiopia;
(C) To support various building blocks of the economy and to reduce the risk of financial
crisis, corporate failure and associated negative economic impacts; and
(D) To ensure that the provision of financial information meets internationally recognized
reporting standards.
17
2.1.2.2 Establishment of the Board
The Accounting and Auditing Board of Ethiopia, established by Council of Ministers
Regulation No. 332/2014 entitled” the Establishment and the Procedure of the Accounting and
Auditing Board of Ethiopia Pursuant to Article 4(1) of the Financial Reporting Proclamation
No. 847/2014. Accordingly, provision of Article 3(1) of the Regulation No. 332/2014
describes. The Accounting and auditing Board of Ethiopia has been established as an
autonomous government organ having its own legal personality (Federal Negarit Gazeta,
2014).
According to Regulation, the board shall be accountable to the Ministry of Finance and
Economic cooperation (Art.3/2 of Regulation 332/2014). Article 5 of the Regulation 332/2014
sets the objectives as:
(A) Promoting high quality reporting of financial and related information by reporting
entities;
(B) Promoting the highest professional standards among auditors and accountants
(C) Promoting the quality of accounting and auditing services;
(D) Ensuring that the accounting profession is used in the public interest; and
(E) Protect the professional independence of accountants and auditors.
The Accounting and Auditing Board of Ethiopia consists of 12 members, which includes one
representative from the following Ministries, governmental agencies and organizations:
Ministry of Finance and Economic Cooperation (MoFEC); Ministry of Justice (MJ), Ministry
of Education (MoE); Ministry of Trade (MoT); Office of General Auditor (OFAG); National
Bank of Ethiopia (NBE), Ethiopian Revenue and Customs Authority (ERCA); Ethiopian
Commodity Exchange Authority (ECEX); Ethiopian Professional Association of Accountants
18
and Auditors (EPAAA), Accounting Society of Ethiopia (ASE), and two representatives from
Ethiopian Chamber of Commerce and Secretariat Associations (ECCSA).
2.1.2.3 Roadmap to IFRS Implementation in Ethiopia
According to AABE (2015), the adoption of IFRS in Ethiopia comprised of three phases. The
following are brief summaries of the three phases.
Phase 1: Significant Public Interest Entities and all Financial Institutions and public enterprises
owned by Federal or Regional Governments at July 8, 2016 is recommended as the date for
adoption of IFRS for financial institutions and large public enterprises. The choice of July 8,
2016 is anchored on the need to give sufficient period over which to effectively transit to IFRS.
Phase 2: Other Public Interest Entities (ECX member companies and reporting entities that
meet PIE quantitative thresholds) and IPSAs for Charities and Societies for statutory purposes,
by July 8, 2017. This means that all other public interest entities and Charities and Societies in
Ethiopia will statutorily be required to issue IFRS and IPSAs based financial statements
respectively for the year ending July 7, 2018.
Phase 3: small and Medium-sized entities IFRS for SMEs shall mandatorily be adopted as at
July 8, 2018. This means that all Small and Medium-sized Entities in Ethiopia will statutorily
be required to issue IFRS based financial statements for the year ending July 7, 2019 (AABE,
2015).
After the establishment and functioning of AABE, the regulations and procedures on Ethiopian
audit firms became tighter and since then changes in the Ethiopian firms have been witnessed
for example all previous OFAG registrant audit firms are required to be re-registered with
AABE. Furthermore, the regulation provides authority to AABE to conduct inspections and
19
investigations concerning registered public accounting firms, and enforce their compliance
with IFRS/IAS. Hence, all AABE registered audit firms, regardless of size, faced increased
quality requirements after the establishment of AABE. All else equal, increased quality
requirements could lead to higher chances of audit failures, which could in its turn lead to
litigation. Likewise, it may also be presumed that the auditors have increased their effort, which
again should be reflected in the reported audit fee for the year starting from 2017 (AABE,
2015).
2.2 Audit Fee Formation
Audited financial statements constitute internationally accepted means and methods through
which business corporations report their operating results and financial positions. These
documents, on the completion of audit, are accompanied by an audit report prepared by
independent qualified and recognized accountants, expressing their professional opinion on the
fairness of the company's financial statements. The contribution of the independent auditor is
to give credibility to financial statements by attesting whether the preparation of these
statements are in conformity with recognized accounting standards. Hence, most countries
require audited financial statements as part of citizen protection, the existence of such laws has
led to creation of audit market and competition among audit firms. Pricing of audit services has
been an interesting issue for the researchers and different studies were conducted to explore
the factors that determine the audit fee charged by an auditing firm (Anwar & Leghari, 2015)
Mustafa (2017) reported that the audit fee charged is influenced by mainly two factors: Auditor
and Auditee related factors. Auditor dependent factors include auditor size, the reputation of
the auditor, auditor experience, competition in the audit market, industry specialization of the
auditor and big four status of the auditor (Joshi & AL-Bastaki, 2000). While, Auditee related
20
factors comprises of the Audited company size, complexity of operations, risk, and the
profitability of the Auditee company (Cannon & Bedard 2017; Joshi, Bremser & Al-Ajmi,
2008; Ng, Tronnes & Wong, 2018).
Ghosh and Pawlewicz (2008) claimed that traditionally, audit fee studies have ignored the
changes in regulatory and disclosure environments. To understand audit fee formation under
the presence of IFRS, more insight is needed on how fees paid to auditors and regulatory
changes are related. Recently, several studies have showed that the regulatory changes and
audit fee pricing are directly related. Consequently, scholars in the field have identified that the
degree of legal regime strength as additional new determinants of audit fee. For example,
Ghosh and Pawlewicz (2008) have shown that differences in regulatory and disclosure
environments affect audit fee differences across countries, but changes in the regulatory and
disclosure environment within a single country have rarely been addressed ( Vieru et al., 2010).
Similarly, Kim, Liu and Zeng (2012) found evidence that the additional audit fee premium
resulted from changes in regulatory and disclosure environments to be lower in countries with
stronger legal regimes and higher in countries with fragile legal regimes.
2.3 The audit fee Model
The audit fee model is the main theoretical foundation for studying factors affecting the prices
of external audits. Several studies used this model in different research areas such as
investigating the audit fee premium with the effect of Sarbanes- Oxley Act 2002 (Griffin et al.,
2007; Salman & Carson, 2009) and the audit fee premium with the effect of IFRS (De George
et al., 2013; Kim et al., 2012).
21
The Audit fee model developed by Simunic (1980) and he defines audit fees paid by auditee
companies as the product of unit price and the quantity of audit services demanded by the
management of the audited company, where cross-sectional differences in fees can represent
either the effect of quantity differences or price difference. He considered the external audit to
be a subsystem of an auditee's overall financial reporting system, hence audit service is viewed
as an economic good to the auditee, which has substitutes and complements in consumption.
Simunic assumes that the auditee and the auditor are risk-free and they want to maximize their
expected earnings each period. Thus, auditee management seeks to maximize the expected
profits of the financial reporting entity, while the auditor seeks to maximize the expected profits
of the audit firm (Simunic, 1980).
Simunic (1980) theorized total audit costs consist of two parts, which are (i) the resource cost
component, which depends on the level of audit effort and (ii) the liability loss component,
which depends on the expected cost of the client’s business risk. He further assumes that the
potential legal liability of an auditee and auditor to financial statement users drives the design
of external financial reporting systems. Hence, he believed that the benefits are in the nature of
liability avoidance. Existence of these two components will prevail companies to promote the
audit process by increasing the amount of resources used to reduce the expectation of losses in
the audited financial statements (Simunic & Stein, 1996). Simunic analyzed the factors that are
significant in explaining the audit fee using an empirical regression model based on audit fees
and related publicly held data of 397 corporations in the United States. The data were analyzed
using a series of least-squares regressions, where the specification of the regression equations
was derived from the model of audit fee determination. In his audit fee model there are three
factors affecting the audit fees: (a) the size of the auditee; (b) the complexity of the auditee's
22
operations; and (c) client’s audit risk. His tests provide empirical evidence that the scale of the
auditee is the main factor influencing audit fees (Simunic, 1980).
The level of audit fees can be influenced by other general factors, which are indirectly related
to the engagement e.g., the size of audit firm, some big firms in the U.K charge more than
others for auditing companies of similar size and in the same industry (Ling et al., 2014).
Conversely, Simunic (1980) found that the big firms enjoy economies of scale which could be
passed on as lower prices to their clients. Other factors could also have a general impact on the
level of audit fees, i.e., the nature of the market for audit services, the probability of obtaining
non audit work such as, accounting, taxation, and management consultancy services, the
continuity of client, and the reputation of company (Simunic, 1980). Several other studies have
used Simunic’s (1980) model to explain various aspects of the link between audit fees and
auditee attributes.
Prior research has shown that the increase in a client’s complexity and risk are associated with
higher fees paid to statutory auditors (Hay, Knechel, & Wong, 2006). The move to IFRS
increases client’s accounting and reporting complexity and the resources needed for preparing
of the financial reporting. Although it is known that complexity and risk in general increases
fees, it is mainly unknown how IFRS transition affects audit fees. This paper looks into the
fees paid to statutory auditors associated with the companies who implement IFRS for their
first time. This study will mainly use Simunic's (1980) audit fee model and builds on other
factors to determine the audit fees level with the presence of IFRS (Griffin & Lont, 2007)
23
2.4 Empirical Review
Numerous academic literature has investigated the economic consequence of major accounting
regulatory reforms on financial reporting. Several Studies have examined the impact of changes
in statutory laws on accounting and corporate governance regulations on auditing since the
pronouncement of Sarbanes-Oxley Act in 2002 in US and Corporate Law Economic Reform
Program Act of 2004 in Australia. Following the promulgation and passage of the Sarbanes-
Oxley Act in the United States in 2002, Ghosh and Pawlewicz, (2008) and Griffin et al. (2009)
reported an increase in auditing fee. In a similar fashion Salman and Carson (2008) studied the
impact of Corporate Law Economic Reform Program Act of 2004 (CLERP 9) on Australian
company audit fees, found a sharp rise in the audit fees following the enactment and adoption
of these reforms.
The adoption of IFRS worldwide is possibly the most far-reaching public prominence and
confining regulatory reforms ever seen. IFRS is perceived to cause a transformation in financial
reporting regime that leads to increased information disclosure (E. Dodzi, 2015) and other
studies reported similar findings (Ghosh & Pawlewicz, 2008; Griffin et al., 2009; Salman &
Carson, 2008). Studies that analyzed the effect of IFRS adoption on auditing suggest that the
implementation of these new standards come with significant cost implications attributable
primarily to the resultant increased in audit effort and audit risk (Kim et al., 2012; De George
et al. 2013; Jermakowicz & Gornik-Tomaszewski, 2006; Choi & Yoon, 2014). Also, Lyubimov
(2013) identified incremental audit effort and audit risk induced by the regulations, and
concluded that audit effort and audit risk as the major audit fees drivers.
The application of IFRS like The Sarbanes–Oxley Act of 2002 (SOX) demand greater exertion
from auditors. Much effort demanded from auditors in that IFRS are more principle oriented,
24
and are based on fair values which is more challenging relative to the local GAAP, which are
based on rules and historical cost, which call for difficult estimations and higher professional
judgment from auditors. The adoption of IFRS is expected to be more costly during the year of
transition as a result of the greater effort, knowledge, skill and competencies needed to
implement the new standard (De George et al., 2013).
In his research with Australian companies, De George et al. (2013) found that audit fees
increased by 23% in the transition period to IFRS in Australian companies. In this period,
adoption was optional until companies fully prepared for the disclosure requirement.
Furthermore, He suggested increase in the audit effort governed by two main factors. Firstly,
in the year of the adoption of IFRS the auditors will make greater efforts to become aware of
the new standards, so that they can evaluate if these standards have been implemented in an
adequate manner. Auditors are likely to attempt to recover the cost of this increased effort by
increasing audit fees. They expected the increase to be recurring, if the extra audit effort under
the IFRS reporting regime continues, because the auditors are certifying more financial
information necessitated by the increased disclosure requirements of IFRS which, are more
detailed and lead to more disclosure than previous local GAAPs. They reported that the first-
time IFRS-compliant annual reports were about 60% longer than the previous annual reports
(De George et al., 2013).
Secondly, increased efforts due to the implementation of IFRS derives from standards that
require a fair value measurement on certain balance sheet items which increases the exercise
of professional judgment, discretion and subjectivity in the financial reporting process.
Furthermore, the effort is even more greater in African countries facing the challenge of the
absence of a liquid market (Ball, 2006; Roger, Jay & Jeffrey, 2006).
25
In the absence of a liquid market, the auditors should use a different approach and gather more
information to assess the credibility of management estimates. This may give rise to the risk of
material misstatement in the financial statement due to management manipulation, erroneous
reporting, and as a result, ultimately, audit failure (Litigation risk). In order to manage these
risks the auditor will charge higher audit fees. In general, expected legal liability depends on
several key factors including the probability of material misstatements in the financial reports,
the probability that the audit would fail to detect the misstatement, and the probability that the
auditor would incur a legal liability due to an audit failure (Choi & Yoon, 2014).
Kim et al. (2012) in their study they made two competing theoretical assumptions about how
the adoption of IFRS affects audit fee. On the one hand, they argue that the use of IAS/IFRS
as opposed to previous Chinese GAAP, are principle-based and fair value oriented standards
with greater disclosure requirement makes it complex therefore, it entails higher level of
judgment and greater effort from auditors will be required; this is likely to be reflected by
higher audit fees. On the other hand, as proponents claim it, IAS/IFRS may improve the quality
of financial reporting, therefore it may lessen the occurrence of material misstatement in the
financial statements, which consequently lowers both audit effort and audit risk (expected
liability costs), which in effect should reduce audit fees (Kim et al., 2012).
Kim et al. (2012) further observed that the audit fee in the year of adoption is mostly higher
compared to the subsequent years, which they attributed to the time and effort taken by auditors
to learn the new standards and additional audit effort required to review the comparative
financial statement arising from the retrospective application of the new standard (Kim et al.,
2012). Similarly, Cameran and Perotti (2014) in their study on auditors’ fee determination on
the adoption and transition to the international accounting standards (IAS/IFRS), they made an
interesting conclusion in line with the findings by Kim et al. (2012) that IFRS could impact
26
audit fees in two main ways, in the first place, incremental effort is demanded from auditors,
which is expected to result in higher audit fees. Alternatively, if IFRS enhances the
transparency of the financial statement resulting in lower inherent risk then lower audit fees is
likely to be charged. This conclusion by Cameran and Perotti (2014) was based on listed and
non-listed Italian banks from 1999 to 2006 and the outcome reveals that audit fees paid by the
banks were much higher after implementing IFRS.
Hart, Rainsbury and Sharp (2009) examined the impact of IFRS adoption on audit fees in the
private sector firms in New Zeeland and reported that audit fees of the companies increased by
48% in the two years prior to adoption of IFRS and in the year of the adoption. Consistent with
Griffin et al. (2008), a study found that audit fees of New Zeeland companies increased in the
period 2002–2006 and that the increase was associated with the transition to, and adoption of
IFRS in New Zeeland.
2.4.1 Variables
In line with Simunic (1980), different scholars found that the size, the complex nature of the
auditee, and audit risk largely influence total audit fees paid. In addition, Lyubimov (2013)
found that auditor size and changes in regulatory environment are important factor that
influence the audit fees. Therefore, it is important to look into the factors that could influence
the audit fees paid by auditee firms specifically. The following are summaries related with the
factors such as size of the auditee firm, complexity of audit firm operations, risk associated
with a client’s operation and size of the auditor respectively.
27
2.4.1.1 Size of the Auditee
Prior studies on audit fees have found that the size of the company is the most critical
determinant of fees (Beattie, Goodacre, Pratt, & Stevenson, 2001; DeAngelo, 1981; Friis &
Nielsen, 2010; Simunic, 1980). Simunic (1980) argues that audit of bigger firms require extra
audit tests and procedures, more effort and time to test and analyze the company’s large data
and information. Jung, Kim and Chung (2016) ranked size as the most dominant and influential
control variable, which accounts for over 70 percent of all variations in audit fees following a
detailed analysis of existing studies on audit fees. By increasing the auditee size, an external
audit service required to carry out extensive inspection work to ensure proper compliance and
material testing. The size of the auditee is one of the most important factors affecting auditing
effort in large companies. Natural logarithm of total assets of the firm is considered as the size.
Furthermore, Ling et al. (2014) found that the audit fee to be positively related to the size and
complexity of the company. The results of their empirical study revealed that company size
affects the scope and size of the audit work, especially if it involves some troublesome areas,
such as stocks, debtors, creditors. They claimed, both size and complexity have substantial
effects on audit fees, the results of his regression model displayed high value of the adjusted
R- square, which indicated that 90% of the variation in audit fees is explained by both size and
complexity of the company. It was also found that company size has stronger influence on audit
fees than its complexity, based on both the correlation coefficient and the adjusted R square
values (Ling et al., 2014).
2.4.1.2 Complexity of the Auditee’s Operations
Typically, it is believed that the more complex the operations of the auditee, the more difficult
and time consuming it is for auditors to undertake such audit (Hay et al., 2006; Simunic, 1980).
Ling et al. (2014) claim that in addition to the scope and size of the audit work, audit fee is
28
influenced by the complexity of the company, Complexity consists of two main aspects; the
level of decentralization and diversification of the financial reporting entity (Ling et al., 2014).
The degree of decentralization and diversification determines the number of decision centers
in an organization whose activities need to be monitored. Researchers as indicators of
complexity in audit fees models have adopted several variables. Typical among them include
the number of subsidiaries which determines the level of decentralization, the number of
foreign subsidiaries, the number of business segment, the proportion of foreign assets, principal
industry of the client, the nature and structure of the assets such as inventories and receivables
etc. Ling et al., (2014) found that complexity explains about 14% of the variation in audit fees.
Correspondingly empirical evidence shows that complexity of auditee’s operations is an
important variable, which strongly influences audit fees. Complexity and audit fees are mostly
reported to be positively associated. The greater the complexity of the auditee, the higher and
extensive auditing procedures needed to be performed to review the transactions, which
increases the audit fees (Hay et al., 2006).
2.4.1.3 Risk
Simunic (1980) revealed the increased risk for inspection by the client is positively associated
with a large auditor of an external audit firm. In order to minimize audit risk, auditors usually
follow a risk-based approach to auditing. This involves auditors assessing the risks associated
with the client’s business, transactions and systems, which could result in material
misstatements in the financial statements. This approach helps them to focus more attention
and resources on areas that present potentially greater loss exposure. Therefore, the level of
perceived risks associated with a client’s operation determine the degree of audit effort to
devout and the specialized type of audit procedures to adopt. Several measures of risk including
29
inherent risk, liquidity risk, capital risk etc., have been considered by researchers. Furthermore,
unavailability of capital market in Ethiopia amplifies the issues related to fair value
measurement requirements. This has a dual effect on both auditors level of effort and possibility
of litigation risk (Simunic, 1980).
Choi et al., 2010 investigate relations between legal liability regime, audit quality and audit
fees. They find that the strictness of a country’s legal liability regime is an important fee‐
increasing factor. The Ethiopian Financial Report Proclamation No. 847/2014, besides
pronouncing the adoption of International Financial Reporting Standards (IFRS), the Council
of Ministers Regulation No. 332/2014 established AABE with the main purpose of improving
the quality of audits and enforce professional standards, in effect it makes the Ethiopian
auditing environment stricter than it was before (AABE, 2015). According to Choi et al. (2010)
strictness of the regulation have an increasing impact on fees. Therefore, the creation of the
AABE could have increased the quality control requirements imposed on audit firms and these
quality requirements might have forced the audit firms increase the audit effort to minimize the
possibility of potential litigation against the audit firm,. All else equal, increased quality
requirements could lead to higher chances of audit failures, which could in turn lead to
litigation. Nevertheless, the effect of such change have been nullified by selection of study
period similar with the establishment of ABBE. As such audit firms have higher liability after
IFRS, which could lead to an increase in the work performed by auditors, controlling for the
effects of AABE (Choi et al., 2010).
2.4.1.4 Size of auditor
Lyubimov (2013) studied the size of the auditor and its impact on audit fees after the SOX and
his study noted two theoretical perspectives on why SOX would have a differential effect on
30
the fee changes by the Big 4 versus non-Big4 firms and they lead to opposite predictions
namely: investment in quality and market structure arguments.
i. Investment in Quality
This perspective centers on the argument that the Big 4 fee premium is driven by the
decision/need to invest in higher quality auditing. According to this perspective, it is argued
that the Big 4 always has higher quality controls than the non-Big 4 companies (Lennox, 1999
cited in Lyubimov, 2013). Therefore, SOX, which requires higher quality and more costly
audits, is predicted to have a relatively less effect on the fees of the Big 4 firms than on the fees
of the non-big 4 firms. In this case, both Big 4 and non-Big 4 firms need to improve their
quality levels. However, the Big 4 will have to improve by a smaller amount on average, less
than that required by non-Big 4, it should therefore require a smaller increase in effort and cost
on the part of Big 4 firms. This, in turn, should lead to smaller fee increases for Big 4 than non-
Big 4 firms after SOX (Lyubimov, 2013).
Along these lines, Choi et al. (2008) examined the impact of a legal liability regime on audit
fees internationally. Within any given legal liability regime, Big 4 auditors charge higher audit
fees, but the Big 4 premium declines as countries' legal liability regimes changed from weak
to strong. The impact of legal regimes on audit pricing and Big 4 premium is more prominent
for small and medium-sized enterprises than for large companies. They argue that regardless
of the regulatory system, Big 4 companies have more resources available, and they can use
those resources to make greater efforts, which is likely to result in higher quality audits (Choi
et al., 2008). Simultaneously, the existence of greater resources also increases the likelihood
that that these auditors will be viewed as a source of “deep pockets” in case of an audit failure.
(Lyubimov 2013)
31
The increased risk of litigation would provide an additional incentive to provide high quality
audit services. These two factors combine to give the big 4 audit firms high quality even in the
SOX environment. Under this argument and the Big 4 is expected to perform high quality
audits under all regulatory regimes. As a result, there is less need to change the burden
following the introduction of IFRS. Hence, Big 4 companies are expected to charge relatively
lower fees for the audit. With regard to companies that are not large, 4 this perspective also
focuses on the resources available to carry out high quality audits. In particular, non-Big 4
companies have fewer resources to consider and invest in the Big 4, which will probably lead
to lower quality testing at the Big 4. Previous research has provided evidence in line with the
claim that the Non-Big 4 companies have a lower quality test (Lennox, 1999 cited in Lyubimov,
2013) and therefore a higher probability of an audit failure.
This perspective focuses on the assumptions that while all companies would need to increase
their efforts after the application of IFRS, non-Big4 firms would be required to make a
relatively greater increase in effort to achieve minimum expectations of regulatory body. In
line with the findings of Choi et al. (2008); De George et al. (2013) showed that the increase
in audit fees is high among small businesses in Australia. It is assumed that non-Big 4 firms
need to have a relatively greater effort, as they work to catch up to the enhanced quality
expectations brought about by the application of IFRS. This view suggests that non-Big 4 firms
will increase the fees more than the Big4 after the introduction of IFRSs (De George et al.,
2013).
32
ii. Market structure arguments
On the contrary, market structure theory views differently, based on the arguments of the
market structure and the role played by such a structure in competition and pricing. The
argument is built on the existence of a bifurcated market for audit services. According to
Lyubimov (2013), in one market segment dominates an oligopoly, while in the other segment,
producers face a more competitive structure. These differences in market structure and
competition have implications for the pricing of the audit Services. In terms of the structure of
the market, the upper end of the market is characterized by the dominance of big-4 companies,
the market for smaller clients is not as highly concentrated (Lyubimov, 2013).
Simunic (1980) suggested the audit market can be characterized as being comprised of two
distinct segments: one more oligopolistic and the other more atomistic in nature. In the first
case only four huge providers of the Big 4 audit service dominate the segment, which consists
of large clients, thus, it is oligopolistic. The atomistic segment refers to the medium and
especially the small client segment where there are many more audit firms and thus the non-
Big 4 or any other provider are likely to have less pricing power. The economics of market
structure posits that the firms in an oligopoly are price setters, as opposed to price takers. One
of the main concerns related to the oligopolistic market structure is a possibility of tacit
collusion, a type of collusion in which several firms in an industry coordinate their production
and pricing decisions by observance of each other’s competitive actions and responses
(Lyubimov, 2013).
As such, the structure of the oligopolistic segment of the audit market fits the characteristics of
an industry where tacit collusion can take place. This is relevant to pricing because tacit
collusion has been shown to lead to abnormally high prices (Friis & Nielsen, 2010). This leads
33
to an assumption that audit fees would be increasing at a higher rate in the oligopolistic segment
of the market. Further, since this segment is presumably dominated by price setting on the part
of the Big 4 firms, fee increases would be higher for the Big 4 than non-Big 4 firms. Lyubimov
(2013) claims that SOX changed the regulatory regime and increased legal liability of all
accounting firms and hypothesized that the associated potential legal liability costs will be
higher for the Big 4 firms because they have more resources to pay legal settlements.
Furthermore, DeAngelo (1981) claimed that the Big 4 have higher reputations at stake in case
of any audit failure. As such the Big 4 firms could be expected to increase their effort more
than non-Big 4 to avoid any possible litigation; increased effort is expected to lead to increased
audit fees. As such, this view suggests that after the adoption of IFRS, the Big 4 would increase
audit fees more than non-Big 4 (DeAngelo, 1981).
Lin and Yen (2016) found that the increase in audit fees for Big4 customers is much larger
after the introduction of IFRS in China. Consistent with Lin and Yen (2016) as well as Choi
and Yoon (2014) showed that audit fees charged by Big4 after the introduction of IFRS in
South Korea have increased significantly. Risheh (2014) showed similar results among
Jordanian listed companies. One possible reason is that non-Big4 audit firms lack the
competence to extend professional judgment and the need to extend more effort than the Big4
dealing with the complexity of IFRS.
Konadu (2018) argued that in developing countries, the Big 4 are always seen as superior in
providing quality auditing services to multinational and large companies. In addition, local
companies in developing countries usually lack professional workers and work experience, so
they cannot compete with Big4. It is clear that companies in developing countries cannot enjoy
the services of the Big4 without the necessary concomitant of high audit fees. Due to the intense
34
competition over the few large non-multinational companies, non-Big4 firms attempt to
bargain on how to stay in business. Consequently, Africa being a developing continent provides
a more competitive advantage for the Big4 in terms of audit prices (Konadu, 2018).
In the first assumption as soon as the regulatory regime has changed, IFRSs have increased
legal liability and the risk of controls / sanctions has led the AABE to stricter auditing
requirements. Under these new conditions, non-Grade A firms have to make major adjustments
to increase the quality of their audits and reduce the risk of litigation. This raises the possibility
that GradeA companies will have to slightly increase their efforts to carry out higher quality
jobs, leading to a slight increase in fees.
While the second assumption claims that the local companies in developing countries usually
lack professional workers and work experience, so they cannot compete with big 4 firms,
hence, the big4 firms have the bargaining power in setting prices. In addition The big4 firms
have higher reputations at stake in case of any audit failure and the fact that potential legal
liability costs will be higher for the Big 4 firms pressure them to exert more effort than the
counterpart non-big 4 hence the resultant audit fee will be higher.
35
CHAPTER THREE
METHODOLOGY
3.1 Overview
This chapter addresses the overall research design, the execution strategy and the
methodological approach followed in conducting this study. It entails the research paradigm,
the sample design, the empirical research models and the method of data analysis applied in
the study.
3.2 The Research Design
The research design defines how a study is designed, conducted and how the results are
translated to capture and clarify the phenomena based on ontological and epistemological
positions. The relevance of the research design in academic research is that it provides scientific
orientation and guidance on selection criteria, according to which all issues, strategies and
methods can be adequately legitimized. Therefore, the study used correlational research design
with quantitative data collection and analysis to examine the impact of the adoption of IFRS
on audit fees. As part of the strategy selection, the study used audited financial statements of
banks which is publicly available on the banks’ website. In addition to this supplementary data
was extracted manually from the published annual reports and the panel regression analysis
used to analyze the data.
36
3.3 Sampling Design
3.3.1 The Target Population
The study is aimed at Ethiopian Financial Institutions specifically the banking industry. One
benefit of using data from a single industry is that the analysis does not suffer from the industry
effect problem (Ajekwe & Ibiamke, 2017; Cameran & Perotti, 2014). Selection of the banking
industry is influenced by different reasons, however, due to that all Ethiopian banks are obliged
to use IFRS in their annual accounts. This allows to examine the impact of adopting IFRS in a
dataset regardless of size of the bank. Therefore, the population of the study is all commercial
banks, private and public, operating in Ethiopia.
A further interesting specificity is that the banking sector is highly regulated towards selection,
appointment and termination of audit firms by the bank. According to the national bank of
Ethiopia directive SBB/19/96 3.2(C) the auditor is not allowed to represent the bank either
directly or indirectly. Thus, in general, the extent of audit fees paid is not significantly
influenced by the possibility of obtaining or maintaining the audit engagement for other non-
audit services.
In order to conduct a pre, conversion and post IFRS adoption impact analysis, the sample
selection covers firms within the target group with at least two years operational existence in
Ethiopia prior to the year 2016.
The year 2016 marked the official year of the introduction of IFRS in Ethiopian financial
institutions and large public enterprises. The Accounting and Auditing Board of Ethiopia
(AABE) announced a three stage Roadmap to IFRS Implementation in Ethiopia in 2015 that
Significant Public Interest Entities and all Financial Institutions and public enterprises owned
37
by Federal or Regional Governments of Ethiopia were required to convert its closing balances
at June 30, 2016 to IFRS-based figures which then become the opening balances as at July 1,
2016 for IFRS-based financial statements as at June 30, 2017.
This means that according to the roadmap, all financial institutions and government owned
(Federal and Regional) public enterprises in Ethiopia will statutorily be required to issue IFRS
based financial statements for the financial year ending July 7, 2018 making 2016/17 as
comparative year
3.3.2 Sampling Technique
According to Edmond (2016), it is impossible to study everybody everywhere and do
everything when conducting research. He also posit that, it is virtually unattainable for
researchers to gather data from all categories being investigated. Therefore a researcher must
endeavor to obtain evidence from a section of the population through a sampling technique.
In order to conduct a pre- and post-IFRS adoption effect analysis, the study employed
purposive sampling technique in the selection of firms for the study. Eventually, 17(seventeen)
commercial banks that satisfy the aforementioned requirement selected, one bank with
incomplete set of annual reports were excluded from the sample. Data was collected on each
sample firm over the study period. This constitutes eighty (80) firm-year observations covering
a period of five (5) years from 2014 to 2018.
3.3.3 Sample Size
The population for this study is made up of all the commercial Banks operating in Ethiopia as at June
30, 2018. The sample size encompasses firms in financial sector. Presently there are 20 banks in
Ethiopia out of which 18 are commercial banks. Thus, with the exception of the Commercial Bank of
38
Ethiopian (CBE), 17 commercial banks has been included in this study. The CBE has been excluded
from the sample due to that yearly financial report of the bank has not been available for selection.
3.4 Study Period
The study covers five-year period from 2014 to 2018. The choice of this period is motivated by several
reasons; first, by the need to conduct an analysis of pre- and post-IFRS adoption effects. In Ethiopia
following the Financial Report Proclamation No. 847/2014; banks’ started adopting IFRS in the years
2016 and 2017, and prepared first full IFRS compliant financial statement in the year 2018; However
the conversion period is known for its complexity for and high costs (P. A. Griffin et al., 2009; Hart,
Rainsbury, & Sharp, 2009) therefore, the impacts of adopting IFRS will be reflected on Audits fees not
only in the year of adoption but also in the conversion periods too; hence in order to conduct the Pre-
and Post IFRS analysis and to inspect the accurate change; the period starting from 2014 will be used
as the study period. The other major reason is that the establishment of the regulatory body AABE in
the year 2014 is believed to have impacted the auditing environment. To satisfy the quality requirements
of AABE, all audit firms increased their efforts; as a result they might have also increased the audit
fees. Therefore to control the effect of change in regulatory environment, the study period
matched with year of AABE establishment; therefore all the years studied (2014-2018) are of
the same level of regulatory requirement complexity. Similar studies in other jurisdictions used
study periods ranging from two (2) to seven (7) years. Europe (Kim et al., 2012), Australia (De
George et al., 2013), Finland (Vieru & Schadewitz, 2010), Malaysia (Yaacob & Che-Ahmad,
2011), Ghana (E. Dodzi, 2015).
39
3.5 Data Collection Procedures and Data Source
3.5.1 Data Collection Procedures
Data was manually extracted from annual reports of banks and using MS excel the data was
classified, summarized and exported to the Stata and SPSS software for further analysis.
3.5.2 Data Source
This study used secondary data; the audited annual financial statements of banks selected for
the study. The data is gathered from the audited annual financial statements of the selected
Banks over the study period. Audited Annual reports of sampled Banks from 2014 to 2018 was
downloaded in soft copy format from the banks official website. However, audited annual
reports of some banks were unavailable online, in such instances hardcopy documents were
obtained directly from the banks or other sources.
Although the study is dependent solely on secondary data drawn from financial statements of
banks; this source is regarded as objective, reliable, unobtrusive and free from response biases
from individual respondents in the case of interviews and questionnaires.
Apart from these advantages the regulatory framework governing the preparation of company
annual reports helps ensure that the annual report is a reliable and attested public document.
The downside associated with this source of data is that the researcher has no control over the
quality of the data (Edmond, 2016). In an attempt to authenticate these documents, data was
only obtained from official website of the banks or directly from the banks.
3.5.3 Population Inclusion Criteria
The inclusion criteria of sample is based on the banks satisfying the following requirements;
Commercial bank operating in Ethiopia; Operational existence since 2014; adopted IFRS as
40
per the AABE roadmap; and that provided complete set of relevant data. The key criteria for
selection was that banks which hitherto prepared their annual financial reports in accordance
with the historical cost convention, generally accepted accounting principles and the laws and
regulations of Ethiopia including the Commercial Code of Ethiopia 1960, Banking Business
Proclamation No. 592/2008 and the Directives of the National Bank of Ethiopia for at least two
years before switching to the use of IFRS with continued operational existence throughout the
study period (2014-2018). Based on this all 18(eighteen) commercial banks were planned for
selection, but on further refining of data availability the CBE has been excluded due to
incomplete publicized annual reports.
3.6 Research Model
In relation to the first objective and to test the first hypothesis, the study adapts the conventional
audit fee regression model developed by Simunic (1980) which has been adopted, modified
and used in several prior audit studies (Cameran & Perotti, 2014; Choi & Yoon, 2014; De
George et al., 2013; Griffin et al., 2009; Kim et. al., 2012; Vieru & Schadewitz, 2010). These
studies guide the selection of variables used in the model. To analyze the effect of the test
variable (IFRS) the researcher compared audit fees during the pre and post IFRS using an
Independent t-test. To address the main objectives of examining whether IFRS adoption among
the sampled banks has affected audit fees, the study employs panel regression analysis.
Secondly, the researcher employed multivariate analysis to examine and explain the combined
effect of size, audit task complexity, risk and IFRS in explaining the change in audit fee
following IFRS adoption. To achieve this IFRS-indicator dummy variable was introduced into
the regression estimation models for audit fees while controlling for other determinants in line
with prior audit literature.
41
3.6.1 Specifications of Model Variables
In line with prior studies, the variables that would be considered for the estimation model and
how they will be measured is discussed below.
3.6.2 Models for total fees paid to the statutory auditor
To examine the first hypotheses, Simunic’s audit fee model is used to analyze whether the IFRS
adoption is related to the total fees paid to auditors. in this research, fees for audit services is
used as a dependent variable and fundamental variables such as auditee size, client complexity
and client risks are used as control variables because these fundamental variables have
significant impact on level of audit fees charged. (Edmond, 2016; J. B. Kim et al., 2012; Vieru
et al., 2010).
However, the variables used in the Simunic 1980’s model are insufficient to indicate the real
impact of audit fees (Phang, 2015; Yaacob & Che-Ahmad, 2012). Hence the model is modified
to include the changes in accounting and auditing regulatory environment.
Figure 1 Audit fee model
42
Empirical evidences show that systematic differences in audit fees exist among different audit
firms. For example Dogzi 2015 has reported that big 4 firms’ charge higher fees in many
countries than that of non-big 4. In line with (Dodzi, 2015; Yaacob & Che-Ahmad, 2012), an
indicator variable is included on the audit fee model to control the possible pricing or effort
differences between Grade-A firms and non-Grade-A audit firms.
3.6.3 Audit Fees
In this research Audit fees mean all charges that the companies pay to the external
auditors against the audit services. Other fees for non-audit services, like management
advisory and consultation are excluded. Auditing fees consist mainly of the wages and
benefits of office and field personnel, travel costs, and other costs necessary to the audit
and related support activities. The fees equal the estimated cost of staff time and the actual cost
of travel for those activities, plus margin of profit. Total audit fee is a dependent variable in the
estimation model. The natural logarithm of audit fees (AF) will be used to in line with prior
studies (Fields et al., 2004 Griffin et al., 2009; Kim et. al., 2012; De George et al., 2013; Vieru
& Schadewitz, 2010; Choi & Yoon, 2014; Cameran & Perotti, 2014).
Therefore, the empirical model for this study is based on previous analysis models by Cameran
and Perotti, (2014) and De George et al. (2013); while specifically this model relates fees paid
to the size, complexity, auditor type, and the risk of the audit client considering the change in
regulatory environment.
3.6.4 IFRS
The variable of primary concern, the IFRS variable, is a dummy variable given the value 1 if
the financial statement comply with IFRS and 0 otherwise. The variable is measured by
43
reading the introduction to the note specifying accounting practice. Here it is stated whether
the accounts are prepared according to IFRS standards or in accordance with generally accepted
accounting principles on historic cost convention and the laws and regulation of Commercial
Code of Ethiopia 1960, Monetary and Banking proclamation No 83/1994, and supervision of
Banking Business proclamation No. 592/2008 and the directives of the National Bank of
Ethiopia.
A number of banks made a successive transition to IFRS during the years 2016 and 2017.
During that period their financial statements are registered as being prepared in accordance
with the generally accepted accounting principles on historic cost convention and the laws and
regulation of Commercial Code of Ethiopia 1960. In this study IFRS compliant financial
statement is where the notes to the financial statement explicitly specify that the financial
statements are prepared in accordance with International Financial Reporting Standards
(“IFRS”) as issued by the International Accounting Standards Board (“IASB”).
Based on prior research it expected that IFRS will have a positive association with audit fees.
The following control variables is considered:
3.6.5 The Size of an Audit Client Company
Previous studies have frequently indicated that the most important variable in explaining the
level of audit fees is the size of the auditee. In these studies the company size is assumed to be
related to the need for more time, resources and effort in preparing, analyzing and testing the
company information before the issuance of audit opinion (e.g. Simunic 1980; Palmrose 1986;
Davis et al.1993; Bell et al.2001; Chung and Narasimhan 2002; Cobbin 2002). In Cobbin’s
44
(2002) survey of auditing literature, the size variable is always reported as a significant
and positive determinant of audit fees.
To capture and measure company size, financial statement items such as the natural logarithm
(log) of total assets or turnover is often prominently used as a proxy variable. In this study the
natural logarithm log of ending total assets is used as proxy for auditee size (SIZE). This
measure is more widely used. All things being equal, the larger the size of the bank the higher
the audit fee (Lin and Yen, 2009). The study therefore predict a positive coefficient on SIZE.
3.6.6 Audit Complexity
The results of many earlier studies support the idea that the client’s complexity is a significant
variable in determining the level of audit fees (Simunic 1980; Niemi 2002; Whisenant et al.
2003; Nikkinen and Sahlström 2005; Joshi and Al-Bastaki 2000)
Vieru and Schwartz claim that the complexity of the auditee increases the need to spend time
and conduct larger and deeper testing procedures and analyses.
The complexity can be related to asset structure and business operations often it is controlled
using two commonly used variables: 1. the ratio of the accounts receivable to total assets or the
ratio of loans and advances to total assets in case of banks (REC) and 2. The square root of the
number of Branches (SQBRA). For complexities in asset structure and business operations
respectively
Simunic (1980) and Francis and Simon (1987) suggest that receivables and inventories require
subjective judgment and consume more time in determining their values and, accordingly, are
difficult and risky to audit. Complexity increases also if the company has numerous
subsidiaries and other entities within the group (Simunic 1980).
45
In this study and in line with Griffin et al (2009), Vieru and Schwartz, Kamal Naser Rana
Nuseibeh, (2008) auditee complexity is captured using the ratio of accounts receivable to total
assets (REC). Since high number of receivables present higher complexity for auditors and the
fact that IFRS7 (Financial Instruments) and ISA 3301, ISA 500.2 requires the auditor to assess
the provisions made for receivables and make conformations on the outstanding receivable
balances, it requires longer time; and the increase in number of branches present higher
complexity for auditors for the fact that the auditor needs on a sample basis review the internal
control system on branches and make annual counts and reconciliations with head office
present a greater complexity for auditors. Therefore, it is expected that number of branches and
amount of loans and advances will be positively associated with the dependent variable audit
fee.
3.6.7 Risk
Audit risk is also an important element in determining the level of audit fees (Simunic and
Stein 1996; Pratt and Stice 1994; Bell et al., 2001). According to Vieru et al., (2010), risk can
arise in different ways. The risk component is related to the auditor’s potential future loss due
to the possibility of litigation or a client’s failure. Audit risk can be defined as the risk that
financial statements may be materially misstated after the audit is completed and an unqualified
opinion issued (Arens and Loebbecke 1994). Audit effort and audit risk are related since
auditors address some forms of business risk by increasing audit effort, which in turn causes
higher audit fees. This implies that the higher the anticipated audit risk the more numerous the
46
audit tests perceived as necessary. In addition, a higher fee is required to compensate for the
greater anticipated risk of audit failure.
Risk variables are controlled for using profitability risk measures, liquidity risk measures and
financial risk measures.
Client profitability: Client profitability reflects the extent to which an auditor may be exposed
to a loss in the event a client is not financially viable and eventually fails (Simunic, 1980). Poor
profitability and high level of variability in profits may lead to greater risk and greater amount
of audit work. Companies that report losses in the recent period’s financial statement may
influence the auditor’s judgment of risk. The poorer the performance of the firm, the higher the
risk for the auditor and the higher audit fee would be expected. On the other hand, some
researchers argued profitable firms have more transactions related to the income and expense
accounts thus the auditor need more time and effort to inspect those accounts, leading to a
higher audit fee (Naser et al. 2007). Studies use various measures for profitability for example;
(Simunic 1980; Ireland and Lennox 2002; Caneghem 2010) used current period loss and find
significant relationships. Others e.g. (Ebrahim 2010; Afesha 2014) using ROA reported
profitability significantly influence audit fee. In this study only ROA is used to measure banks
profitability for the fact that all banks under study did not report loss during the study period.
A direct relationship between banks profitability (ROA) and audit fees expected.
Liquidity risk: Liquidity risk relates to the possibility that the bank cannot meet its obligations
for cash through the clearing system or from its depositors. Fields et al., (2004) noted that banks
with large numbers of transactions accounts necessarily have much more complex activities
47
that are costly to perform and monitor; one of the famous ratios of liquidity is current ratio;
current ratio measures liquidity as a proportion of current assets and current liability (CR).
Afesha (2014) measured liquidity risk as the relationship between liabilities with a maturity of
less than one year to those with a maturity of more than one year. In this study liquidity is proxy
by current assets to current liability and demand deposits to total deposits. Based on the above
arguments liquidity risk as measured by LIQ and CR is expected to have a positive relationship
with audit fees in this study.
Financial risk: Financial risk relates to the possibility that the bank cannot meet its long term
fixed financial obligations. It is a key measure of business solvency, it shows how the company
is leveraged or it measures the assets of a company relative to its liability. In this study leverage
(LEV) is computed as the ratio of debt to total asset, lower debt ratio suggests the company is
less leveraged and has strong equity position. Hence it is expected to have a positive
relationship between financial risk and audit fee.
3.6.8 Auditor Type
Studies on the determinants of audit fee have found evidence of a large audit-firm (Big 4)
tendency to charge fee premium this premium has been interpreted as an indication that large
audit firms, considered as a group, receive higher fees than non-Big firms because they are
perceived to provide higher quality audit services (Simon, and Francis, 1988). Similarly
Craswell et al., (1995) found that specialist Big 8 auditors earn a 34 percent premium over non-
specialist Big 8 auditors. To identify the biggest audit firms in this market, there are different
ways which could be used, such as the firm's number of partners, number of firm's BIG clients,
the firm's average fees, and the profitability per partner etc. But unfortunately such information
is not publicly available. The criterion used in this study is the grade of audit firms as published
48
by The Office of The Federal Auditor General (OFAG) with effect from July 2014. To control
for the potential effect of Grade A versus non-Grade-A auditors a dummy variable is used with
a value of 1 if the current years audit is conducted by Grade-A auditors and 0 otherwise.
3.7 Empirical Estimation Models
The study adapts audit fee model used in previous studies. Accordingly the audit fee regression
model to be used is specified as:
AFit = β0 +β1IFRSit + β2SIZEit +β3RECit +β4CRit +β5LEVit +β6ROAit + β7LIQit +β8GradeAit
+β9SQBRAit +Ԑ .................................................................eqn (1)
Where,
AFit represents natural logarithm of the audit fees of bank i for year t
IFRSit represents a dummy which takes a value of 1 if the audited financial statement of bank
i for year t is IFRS compliant, 0 otherwise
SIZEit represents the natural logarithm of total assets for bank i for year t
RECit represents the ratio of total loans and advances to total assets for bank i for year tCRit
represents the ratio of current assets to current liabilities of bank i for year t
LEVit represents the ratio of total liabilities to total assets of bank i for year t
ROAit represents the ratio of net income to beginning total assets of bank i for year t-1
LIQit represents the ratio of demand deposits to total deposits of bank i for year t
GRADEAit represents a dummy which takes a value of 1 if auditor of bank i for year t is a
GradeA Auditor, 0 otherwise
SQBRAit represents the square root of the number of Branches for bank i for year t
Ԑ represents the error term
3.8 Method of Data Analysis
In relation to the first objective and to test the first hypothesis, the study adapts the conventional
audit fee regression model developed by Simunic (1980) which has been adopted, modified
and used in several prior audit studies (Griffin et al., 2009; Kim et. al., 2012; De George et al.,
49
2013; Vieru & Schadewitz, 2010; Choi & Yoon, 2014). These studies guide the selection of
variables used in the model. To analyze the effect of the test variable (IFRS) the researcher
compared audit fees during the pre and post IFRS using an Independent t-test. Secondly, to
address the main objectives of examining whether IFRS adoption among the sampled banks
has affected audit fees, the study employed multivariate panel regression analysis to examine
and explain the combined effect of size, audit task complexity, risk and IFRS in explaining the
change in audit fee following IFRS adoption. To achieve this IFRS-indicator dummy variable
was introduced into the regression estimation models for audit fees while controlling for other
determinants in line with prior audit literature.
3.8.1 Resolving Methodological issues
3.8.1.1 Multicollinearity Problem
Multiple linear regression analysis is expected mainly to conduct collinearity diagnostics,
which enables to detect inflated linear relationship that give two values—Tolerance and VIF
(variance inflation factor) and both are related to each other in the way that tolerance is just the
reciprocal of VIF. Tolerance, which is simply 1 minus that R2, very low values of tolerance
(0.1 or less) indicate a problem. Very high values of VIF (10 or more) indicate a problem.
According to Gaur and Gaur (2009), once multicollinearity is detected in the model, the
regression coefficients are likely to be meaningless. One may consider removing some
independent variables, which are highly correlated to reduce multicollinearity or
standardizing/transforming the predictor variables. A value of VIF higher than ten (or
Tolerance less than 0.1) indicates the presence of multicollinearity (Gaur & Gaur, 2009).
Besides, Vieru & Schadewitz (2010) suggests a variance inflation factor, VIF>10 as a guideline
for serious multicollinearity.
50
Table-1: Multicollinearity Analysis Statistics
Variables VIF Tolerance*
SIZE 2.43 0.41
CR 2.42 0.41
LEV 2.32 0.43
REC 2.18 0.46
IFRS 1.24 0.81
ROA 1.22 0.82
LIQ 1.15 0.87
GradeA 1.13 0.88
Mean VIF 1.76
Note: VIF- Variance inflation factor *Tolerance = 1/ VIF
The highest correlation among the independent variables in the audit fee model is achieved
between SIZE and SQBRA with a positive coefficient of 0.84. By rule of thumb, a correlation
coefficient above a threshold of 0.5 suggests possible existence of multicollinearity problem.
Notwithstanding, literature argues that once the coefficient is not above 0.8, it indicates
minimal multicollinearity which is not a threat (Apadore & Noor, 2013). As a result the
SQBRA has been removed from the model due to the VIF (25) and Tolerance (0.04) values
were outside of the accepted collinearity range. Therefore, in the current analysis, after
removing SQBRA, the test results of collinearity values (refer Table-1) of minimum and
maximum of each tolerance and VIF (1.13 - 2.43 and 0.88 - 0.41) respectively. This suggests
negligible or no significant effect of multicollinearity problem among the variables on the
results.
Based on the above results of VIF the revised model is stated as:
AFit = β0 +β1IFRSit + β2SIZEit +β3RECit +β4CRit +β5LEVit +β6ROAit + β7LIQit +β8GradeAit +Ԑ
.................................................................eqn (2)
51
3.8.1.2 Levene’s Equality of Variances Test
In order to check the normality of the sample distribution Levene’s test has been conducted.
The output of the test (F = 0.16, p=0.69) ascertains the data of sample distribution is parametric
would have been tested using nonparametric test (refer Table 5 in chapter 4).
that rejects the H0 (equality of means). Had it been the F-ratio statistically significant the data
52
3.8.1.3 Normality
Also, to enhance the normality of the data and minimize the effect of anomalies in the data set,
the natural lo
Figure 2 Normality plots
53
logarithm function is applied on audit fees, and company size (total assets). Furthermore, Size
of audit firm Grade A is dummy in addition to the IFRS variable.
3.8.1.4 Haussmann’s Specification Test
Multivariate regression analysis requires erogeneity of the independent variables. The problem
of indogeneity occurs when an independent variable is correlated with the error term in a
regression model. The Haussmann’s specification test is conducted to determine whether
correlation exists between the error terms and the explanatory variables, and to know the
appropriate regression model whether fixed or random effect models to use. As indicated in
Table 2 the results of the Haussmann’s test suggests Random effects model if the p-value
greater than 0.05, hence in this analysis Random effects model is used.
Table 2: Haussmann’s Specification Test
Coefficients
Difference
(b-B) sqrt(diag(V_b-V_B))
S.E.
Fixed
(b)
Random
(B)
IFRS 0.286 0.216 0.070 0.033
SIZE 0.162 0.292 -0.129 0.070
REC -0.418 -0.967 0.548 0.297
CR -0.355 -0.259 -0.096 0.046
LIQ -1.100 -0.996 -0.104 0.400
ROA -1.745 -1.047 -0.698 0.963
LEV 3.707 3.658 0.049 0.460
GradeA 0.179 0.124 0.055 0.032
chi2 = (b-B)'[(V_b-V_B)^(-1)](b-B) = 6.44
Prob>chi2 = 0.5984 (V_b-V_B is not positive definite)
3.8.1.5 Robustness Check
In statistical analysis, because residual errors resulting from using sample data in predicting
parameter estimates are deemed to equate the true error in a population, it is important that the
54
population exhibits a random and an equal or constant variance across all observable units or
elements within the population. Homoscedasticity alludes to the assumption that dependent
variable(s) exhibit equal levels of variance across the range of predictor variable(s) so that the
variance of the dependent variable being explained in the dependence relationship should not
be concentrated within only a restricted range of the independent variables. Thus, the
requirement of homogeneity of residual variances or homoscedasticity is critical to the proper
application of many multivariate techniques such as multiple regression analysis. When the
variance of the error terms appears constant over a range of predictor variables, the data are
said to be homoscedastic. If the dispersion or spread of the variance is unequal across values
of the independent variables or when the error terms have modulating variance, the data are
said to be heteroscedastic. Heteroscedasticity or non-constant error term causes a problem in
estimation as it renders the estimate values for the Adjusted R-square and F-statistic unreliable.
Therefore, to address inconsistencies that might exist in the data set resulting from
autocorrelation and heteroscedasticity robustness check test has been conducted. To check for
the possible presence of heteroscedasticity, tests like Cameron & Trivedi's decomposition of
IM-test and Breusch Pagan Cook-Weisberg test for heteroscedasticity were conducted and in
both cases the P-value is above the α level which otherwise would have rendered the regression
results spurious, a robustness check is conducted using robust regression.
55
CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION
4.1 Introduction
This chapter presents analysis of the data gathered and a discussion of the results. The chapter
entails the descriptive analysis of the summary statistics of the data, correlation analysis and
the presentation and discussion of the regression results and findings.
4.2 Descriptive Analysis
4.2.1 Descriptive Analysis on Audit fees
The summary statistics for each variable used in the regression models are displayed in Table
3 below. In the regression analysis the natural logarithm of audit fees, and of total assets (SIZE)
are used. The variables with minimum and maximum values of 0 and 1 respectively are
dummies. The other remaining variables are computed as ratios.
Table 3: Variables Summary Statistics
Variable Obs Mean Std. Dev. Min Max
AF 80 12.1374 0.6654 10.6201 13.4225
IFRS 80 0.2000 0.4025 0 1
SIZE 80 22.9417 0.9609 20.5895 24.7355
REC 80 0.4765 0.0622 0.2929 0.6739
CR 80 1.1438 0.1913 0.1069 1.6142
LIQ 80 0.2883 0.0672 0.1501 0.4640
ROA 80 0.0336 0.0096 0.0034 0.0624
LEV 80 0.8459 0.0433 0.6900 0.9200
GradeA 80 0.6875 0.4664 0 1
AF_Birr 80 231,422 156,259 40,950 675,000
56
4.2.2 Annual Audit Fee Statistics
This section presents analysis of the audit fee data along pre and post IFRS adoption era. The
statistics from table 4 below shows evidence of an overall increase in audit fee for the entire
study period. The sampled banks on average, saw huge increase in the mean audit fees from
ETB 185,732 in pre-IFRS adoption period to ETB 321,534 in the post adoption period
representing about 73% percent compared to, a 25% increase in the mean audit fees from ETB
185,732 in pre-IFRS adoption period to ETB 232,057 in the conversion period and also there
is a 39% increase in the mean audit fees from ETB 232,057 in the conversion period to ETB
321,534 in the post adoption period.
The statistics on audit fees have generally shown an increase in the average yearly fees. The
year on year statistics show that the mean audit fees for the entire sample increase from ETB
176,464 in 2014 to ETB 321,534 in 2018. Thus, although fees have generally increased year
after year, over the period of five years from 2014 to 2018 audit fees have increased by about
82%. The yearly swings in fees can be ascribed to a number of factors ranging growth and
expansion in the size and operations of the banks to changes in general economic conditions.
Table 4: Annual Audit Fee Statistics
Panel A year to year summary
Over periods Mean Std. Err. [95% Conf. Interval]
2014 176,464.40 32,319.62 112,133.80 240,795.00
2015 194,998.80 33,869.22 127,583.80 262,413.70
2016 223,113.40 39,803.36 143,886.80 302,340.00
2017 241,000.60 38,177.67 165,009.90 316,991.40
2018 321,533.80 44,293.11 233,370.50 409,697.00
57
Panel B Periodic summary
Figure 3: Average Yearly Audit Fees for the Sample Banks
The graph above shows a gradual but steady rise in fees from year 2014 to 2016 which became
sharper from fourth year, 2017 when the banks began switching from the previous reporting
local standard, to IFRS.
The sample is further sub-grouped into two: banks audited by the Grade- A auditors and Non-
Grade-A audit firms. From the total 80 firm-year observations, 55 (representing 69%) were
audited by the Grade-A audit firms. Figure 4 below shows the graphic view of the statistics.
As per the graph, the average fee incurred by banks audited by the Grade-A audit firms is
relatively higher than those audited by the Non-Grade A in the pre IFRS period by quite a
Comparison Diff in Birr %change
pre Vs post 135,802.00 73%
pre Vs conversion 46,325.00 25%
conversion Vs post 89,477.00 39%
Years period Mean Af_birr
2014-2015 pre 185,732.00
2016-2017 conversion 232,057.00
2018 post 321,534.00
58
substantial margin. However, in the conversion periods (2016-2017) the average fee charged
by Grade A moves staidly while a sharp rise in the audit fee charged by the non-Grade A firms
and exceeded the average fee charged by Grade A in the year 2018.
Figure 4: Average Audit Fee Based on Grades of Auditor
It is witnessed that banks audited by the Grade A tend to pay higher audit fees than those
audited by Non-Grade-A audit firms. The average audit fee charged for entire period by Grade-
A is 38% higher than charged by Non Grade-A firms. (ETB 183,145 and 253,366). Although
this supports arguments that the GradeA audit firms usually charge premium for brand names
associated with superior quality audit; Interestingly the post IFRS adoption incremental audit
fee charged by non-Grade-A auditors is about 62% higher than the incremental fee charged by
Grade A auditors. The incremental charge by Grade-A auditors is about 31% from (ETB
238,873 to 313,413) while the counterpart non-Grade-A auditors is about 136% from (ETB
144,082 to 339,400) post IFRS period. And the average audit fee charged by Non-GradeA
auditors in post IFRS period is about 8% higher than the counterpart Grade-A auditors (ETB
313,413 against 339,400).
59
This shows that in the post-adoption period ceteris parabus, Non-Grade-A auditors tend to
charge more for their audit service than the Grade-A auditors. This observation provide primary
evidence in support of investment in quality assumption which assumes that GradeA always
has higher quality controls than the non-GradeA companies. The assumption further claims
that while all companies would need to increase their efforts after the application of IFRS, the
GradeA will have to improve by a smaller amount on average, less than that required by non-
GradeA, hence the non-GradeA firms need to have a relatively greater effort, as they work to
catch up to the enhanced quality expectations brought about by the application of IFRS as a
result they charge higher fees.
It is observed that not only has the average audit fee increased over the study period but the
extreme least and largest amounts year on year appear to have increased also. Figure 5 below
demonstrated both the minimum and maximum audit fee charged for banks increased gradually
over the study period. Over a period of five years the biggest amount of audit fee charged for
banks has risen from ETB 475,000 to ETB 675,000 while the least audit fee charged for a bank
risen from ETB 40,950 to ETB 131,000 almost three times increase.
Figure 5: Yearly Minimum and Maximum Audit Fee Chart
60
4.3 Pre-Post IFRS Variance Analysis of AF
Analysis of mean difference between pre and post IFRS adoption using independent t-test of
the AF showed statistically significant difference with t(78) = -2.78, p = 0.01. The negative t-
value indicates that increment of the mean AF from pre IFRS to post IFRS adoption with MD
= -0.497. Therefore, the outcome of the t-test shows that post IFRS audit fee is higher than the
pre IFRS audit fee of the client banks.
Table 5: t-test AF Means based on IFRS
Independent Variable
Levene’s Test
Levene's Test t-test 95% CI of D
F Sig. t df MD SED Lower Upper
IFRS 0.16 0.69 -2.78** 78 -0.497 0.179 -0.852 -0.141
Note: MD = Mean Difference; SED = Std. Error Difference ** Significance level at 0.01
4.4 The Correlation Analysis for Audit Fee Model
Pearson’s correlations test was performed to ascertain the levels of association between the
dependent and the independent variables. The correlation analysis of the dependent variable
against the independent variables indicated that with the exception of REC and BIG4, all
independent variables have statistically significant relationship with the dependent variable
(AF). Predictor variables IFRS, SIZE and LEV are directly correlated with AF, whereas, LIQ,
ROA and CR have negatively related with AF. Besides, both groups with exception of ROA
have showed statistically significant relationship with AF at significance value of p = 0.01,
while ROA showed significance at significance value of p = 0.05. However, the predictor
variables REC and GradeA showed insignificant positive correlation with AF; r = 0.02 and
0.07 respectively.
As indicated in Table 6 below, comparative examination on the correlation coefficients among
the predictor variables also showed, except two pairs of predictor variables, correlation
coefficient values less than 0.5. The two pairs that demonstrated r>0.5 are CR and REC and
61
REC and LEV with R-values of 0.53 and 0.57 respectively. However, multiple linear regression
models allow inter-correlation between a pair of independent variables up to 0.8, as noted above
the highest r- values(r = 0.53, 0.57) are less than the general correlation strength tolerance (i.e.
r = 0.8). Therefore, as long as the multicollinearity tests are within the acceptable tolerance
ranges the three independent variables were included into the estimation model. Another
simplest way to ascertain whether or not our explanatory variables are highly correlated with
each other is to conduct a superior measure which is the variance inflation factor (VIF) scores
test, If VIF score ≥ 10 pose serious multicollinearity problem. As reported in Chapter 3 Table
1, the highest VIF scores for each independent variable in the model is 2.43 which is below the
threshold of 10. This suggests no significant effect of multicollinearity problem among the
variables on the results.
Table 6: Correlation Matrix for the Variables in the Audit Fee Model
1 2 3 4 5 6 7 8 9
1 AF 1.00
2 IFRS 0.29** 1.00
3 SIZE 0.80** 0.32** 1.00
4 REC 0.19 0.19 0.21 1.00
5 CR -0.36** -0.01 -0.37** 0.53** 1.00
6 LIQ -0.33** -0.26* -0.21 -0.15 -0.03 1.00
7 ROA -0.24* -0.05 -0.27* -0.18 0.01 0.10 1.00
8 LEV 0.40** 0.07 0.49** 0.57** 0.23* -0.10 -0.40** 1.00
9 GradeA 0.07* 0.03 0.07 -0.07 -0.26* -0.16 -0.10 0.01 1.00
Note: **. Correlation is significant at the 0.01 level * Correlation is significant at the 0.05
level.
62
4.5 The Multivariate Regression Analysis
4.5.1 Random Effect Model Analysis of Audit Fee
In deciding whether the fixed effects model or random effects model is more suitable the data,
the Haussmann’s specification test is conducted. The chi-square (χ2 = 6.44) shows a p-value
of 0.59 which is greater than α of 5%. The null hypothesis (Ho) of the test of no significant
difference between the coefficients of the fixed (βFE) and random (βRE) models (i.e. βFE - βRE)
has produced an output of χ2 = 3.68, p = 0.87). Had this difference been significant (p < 0.05)
the random effect estimator would not have been used. Therefore, this output indicates that the
Ho (difference in coefficients not systematic) is rejected and it is assumed that correlation
between the error term of audit fee model and the independent variables exists. Thus, the
random effects model is used.
63
4.5.2 Regression Results for Audit Fee Model
As demonstrated in Table 7, the independent variables included in the regression estimation
based on the random effect model of the audit fees are IFRS, Size, REC, CR, LIQ, ROA, LEV
and GradeA.
As indicated on Table 7 above, the robust random effect regression model output in the Wald
chi-square value χ2 (8) = 525.66, p = 0.000) this shows that the goodness of fit test statistic and
overall significance of explanatory powers all the independent variables. Therefore, the
statistically significant chi-square values give us an assurance that the random effect estimation
model can be used to predict the AF based on the predicting power of the independent variables.
The overall coefficient of determination, R2 = 0.6610 shows that about 66.1% of the variations
in audit fees can be accounted for by the model. In other words, the collective contribution of
the independent variables to the estimation of AF in the random effect regression model
accounts 66.1%.
Table 7: Random-Effects Regression Results
Random-effects GLS regression Number of obs = 80 Group variable: bnk_id Number of groups = 16
R-sq: within = 0.6573 Obs per group: min = 5
between = 0.6697 avg = 5
between =
0.6697 overall = 0.6610 max = 5
overall
= 0.6610 Std. Err. adjusted for 16 clusters in bnk_id) Wald chi2(8) = 525.66
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 AF Coef. Rob. Std.
Err.
Z P>z [95% Conf.Interval]
IFRS 0.216*** 0.064 3.39 0.001 0.091 0.341
SIZE 0.292*** 0.083 3.53 0.000 0.130 0.454
REC -0.967 0.711 -1.36 0.174 -2.361 0.428 CR -0.259* 0.114 -2.26 0.024 -0.483 -0.034 LIQ -0.996 0.768 -1.30 0.195 -2.502 0.510
ROA -1.047 4.033 -0.26 0.795 -8.951 6.858
LEV 3.658*** 1.069 3.42 0.001 1.562 5.753
GradeA 0.124 0.106 1.17 0.244 -0.084 0.332
_cons 3.312 1.968 1.68 0.092 -0.545 7.168
sigma_u 0.35234925
sigma_e 0.21167395
rho 0.73480729 (fraction of variance due u_i)
Note: ***significant at 0.001 level ** significant at 0.01 level. * Significant at 0.05 level.
64
The above results show that for the most part the model‟s explanatory power is driven by IFRS,
SIZE and LEV.
Further investigation of the influence of independent variables on AF shows that IFRS has the
highest Z-score value with a positive statistically significant coefficient, p-value of 0.000. this
result complies with the independent t-test based on before and after introduction of IFRS that
there exists statistically significant difference between pre and post means of audit fees with t
(78) = -2.7, p = 0.007 and MD between the two IFRS groups is -0.50. The hypothesis is
supported at 1% significance level. Therefore, the null hypothesis that IFRS adoption affects
audit fees cannot be rejected.
This implies that Ethiopian banks pay higher audit fees when they prepare financial statements
in accordance with IFRS than they would suppose the financial statements been prepared in
accordance with the generally accepted accounting principles under the historical cost
convention and industry specific Directives of the National Bank of Ethiopia.
For the control variables, SIZE showed highest significant influence on AF, with significance
coefficient of p = 0.000. The size of the banks has direct relationship with the AFs that those
client banks with bigger size pay more audit fee than those banks with smaller size. Intuitively,
large banks are expected to incur higher audit fees being associated with high volumes of
transactions that require greater audit effort.
Similarly LEV showed a significant influence in AF at 0.1% significance level, significant
positive coefficient show that highly leveraged banks pay more than the less leveraged banks.
This provides evidence of supports the argument that audit firms charge higher fees for risky
firms as a cushion in event of audit failure and possible litigation claims for damages they may
have to pay.
65
The CR have significant negative relationship with audit fees of the client banks at 5%
significance level (refer table-6). The significant and negative coefficient for CR indicates that
audit fees are higher for riskier clients. This means that a bank with low liquidity pays higher
than those banks with a higher liquidity ratios.
The remaining variables REC, LIQ ROA and GradeA showed insignificant coefficients, the
former three have negative relationship with AF while the latter showed positive relationship
with AF.
4.5.3 Further Analysis: Audit Fee Model
The regression output presented in Table 7 above shows that a number of the independent
variables have high probability values which signify their statistical irrelevance in the audit fee
model. In order to retain the regression coefficients (β) of each predictor variables, with
statistically significant Z-value, are taken from the table 7 above and a pair-wise as well as
auxiliary regression analysis is conducted to consider the relative importance of each
independent variable in the estimation model. Accordingly, the predictor variables that have
relative importance are retained while less relevant (irrelevant variables) are dropped out and
dummy interaction variable IFRSGradeA is introduced into the model to assess whether
companies audited by the GradeA audit firms paid higher IFRS related audit fees than those
audited by the non- GradeA. Consequently, the final model become:
AFit =β0 + β1IFRSit + β2SIZEit + β3RECit + β4LIQit + β5LEVit +β6ROAit + β7 GradeAit + β8IFRS
GradeAit +Ԑ ...eqn (3).
66
The regression results using equation 3 are tabulated in Table 8 below.
Table 8: Random effect regression analysis of significant variables
Random-effects GLS regression Number of obs = 80
Group variable: bnk_id Number of groups = 16
R-sq: within = 0.6325 Obs per group: min = 5
Between = 0.7238 avg = 5
Overall = 0.6961 max = 5
(Std. Err. adjusted for 16 clusters in bnk_id) Wald chi2(7) = 896.45
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
AF Coef.
Robust Std.
Err. Z P>z [95% Conf. Interval]
IFRS 0.291*** 0.065 4.49 0.000 0.164 0.418
SIZE 0.397*** 0.074 5.38 0.000 0.252 0.542
REC -1.579** 0.608 -2.60 0.009 -2.770 -0.387
LIQ -0.899 0.733 -1.23 0.220 -2.336 0.538
LEV 2.437 1.366 1.78 0.074 -0.241 5.114
ROA -1.404 4.559 -0.31 0.758 -10.338 7.531
GradeA 0.146 0.111 1.31 0.191 -0.073 0.364
IFRSGradeA -0.186 0.128 -1.45 0.147 -0.436 0.065
_CONS 1.892 2.185 0.87 0.387 -2.391 6.174
Sigma _u .3568328 Sigma _e .2212282 rho .72234934 (fraction of variance due to u_i) Note: ***significant at 0.001 level ** significant at 0.01 level. * Significant at 0.05 level.
Table 8 above displays the robust regression estimation results for the audit fee model for
banks. The result suggests overall fitness of the model for the data with significant Wald’s chi2
values (χ2 (7) = 896.45, p = 0.0000). The overall R2 values (0.6961) indicate that the predictor
variables together explain around 69.61 % of the variations in audit fees. Remarkably, the
results show that the independent variables including the hypothesis variable (IFRS) have
increased their statistically highly significant magnitude of coefficients. Besides, the higher
value of the Wald chi2 values increment from χ2 (8) =585.55 to χ2 (7) = 896.45 shows that this
model has good fitness than the first model. With regards to the hypothesis variable increment
of positive coefficient of the IFRS from 0.216 to 0.291 (both at p = 0001) confirms that banks
generally incur substantially higher audit fee for applying the IFRS. This finding points to the
67
overall complexity of the IFRS standards. IFRS is significantly positive at less than the 0.001
percent level. This is consistent with H1, suggesting that the audit fee is positively associated
with IFRS adoption as a result of the increase in audit complexity brought about by IFRS
adoption. The hypothesis is supported at 1% significance level
The other three independent variables (SIZE, LEV and GradeA) are all positively related with
the dependent variable (AF) while CR, ROA and IFRSGradeA are negatively related, Size and
REC are significant at 0.1 % significance level.
The complexity variable REC surprisingly have negative coefficients, significant at 0.01%
significance level. This observation could be explained by the fast development in the
information systems which makes audit of such assets less complex. Audit of receivable
posed a great complexity in 1980s, while this days audit of such assets are now easier to audit
than intangible assets, especially with the adoption of IFRS accounting standards.
Finally the interaction variable IFRSGradeA, have a negative relationship with audit fees,
albeit insignificantly the negative coefficient indicates that the audit fees charged by GradeA
firms after IFRS adoption is less than the audit fees charged by non big4 audit firms. The
result controverts with the H3 that the GradeA audit firms charge higher fees than non
GradeA firms in post IFRS regime. Therefore, the null hypothesis that GradeA firms charge
more after the introduction of IFRS is rejected.
68
CHAPTER FIVE
DISCUSSION, RECOMMENDATION AND CONCLUSION
5.1 Summary of Findings
This section summarises the findings as follows. First, the study examines the effect of IFRS
adoption on audit fees among commercial banks operating in Ethiopia. The study finds a
significant positive relationship between IFRS and audit fees which shows that IFRS
adoption substantially increased audit fees among commercial banks operating in Ethiopia.
This is attributed to the general complexity of the IFRS. The study also finds that banks
audited by the Non-GradeA audit firm experience greater IFRS audit fee increases than those
audited by the GradeA audit firms
5.2 Discussion
The results of the multiple regression show the following indications: the reported high chi
square value shows the goodness of fit suggesting the model fits the data. The Adjusted R2 of
0.69 indicate that about 69% of the variations in audit fees can be explained by the model. Prior
studies have reported adj R2 value ranging from 60 to 80% (Vrentzou, 2011).
• The variables of primary concern IFRS
As predicted, the coefficient of the primary variable of interest (IFRS) shows a very strong
statistical significance at 1% level in both audit fee models Table 6 and Table 7. Accordingly,
this results support hypothesis 1, which states that the, the transition to IFRS is associated with
an increase in the amount of audit fees. From these results we can conclude that the transition
to IFRS was expensive in terms of auditing of accounts prepared under IFRS. This observation
implies that the adoption and implementation of the new standard (IFRS) have significantly
increased audit fees for Ethiopian banks in the IFRS-compliant period.
This result can be explained by the increase in level of disclosure in the financial statements
and high level of professional judgment. This evidence support the argument that auditors exert
69
extra effort on IFRS based financial statement due the complexity and much disclosures
associated with it.
These results corroborate the results of prior studies on the impact of IFRS on audit fees Hart
et al. (2009), Griffin et al. (2008) Schadewitz and Vieru (2007), Le Maux (2007) and
Jermakowiez and Tomaszewski (2006), Lin & Yen, (2010).
• The size of the firm audited
According to results, the size of the bank seems to have a positive and significant effect on the
amount of fees (Z = 5.38 and P = 0.000), as rightly predicted, the coefficient of SIZE is positive
and highly significant, suggesting that size is positively related to audit fees. The result implies
that audit fees are higher for banks that are bigger in size relative to small banks. This result
corroborates to the results found by (Craswell & Francis, 1999; DeAngelo, 1981; E. G. Dodzi,
2015; S. Kim et al., 2012; Ling et al., 2014; Simunic, 1980).
The study relate this result to the argument by Fields et al. (2004) that large banks are usually
associated with much more complex financial profiles and diverse sources of liquidity than
small banks as well has considerably different risk profiles.
The consistent significance of the positive coefficient on SIZE appear to corroborate the
assertion by Ling et al (2014), that size is by far the most dominant and significant variable
which account for over 70 percent of all variations in audit fees.
This findings also support the assertion by Simunic (1980) that audit of larger companies
require additional detailed audit procedures and tests, more effort and time to test and analyze
the company’s large data and information.
• The Complexity Variable
The coefficient of REC shows negative and significant at 5 percent indicating that banks with
complex operations pay relatively lower audit fees. Contrary to hypothesis 3, the weight of
loans and advances does not seem to have a positive and significant effect on the amount of
audit fees (Z = -2.60 and P= 0.009). This result contrast with the findings reported by (Choi &
Yoon, 2014; E. Dodzi, 2015; Simunic, 1980; Vieru, & Schadewitz, 2010) but corroborates with
the more recent studies (Le Maux 2010; Loukil, 2017). This result can be explained by the
70
increasingly less complex nature of these audit assets. These elements indicated a high risk in
80s, are now easier to audit than intangible assets, especially with the adoption of IFRS
accounting standards.
• Risk Variable
The leverage ratio LEV showed a significant influence in AF at 0.1% significance level,
significant positive coefficient show that highly leveraged banks pay more than the less
leveraged banks. This provides evidence of supports the argument that audit firms charge
higher fees for risky firms as a cushion in event of audit failure and possible litigation claims
for damages they may have to pay. The result supports the argument that audit firms charge
higher fees for risky firms as a cushion in event of audit failure and possible litigation claims
for damages they may have to pay. This finding contradicts Vieru & Schadewitz (2010) who
documented a significant negative coefficient in Finland but agree with other recent results
(Griffin et. al., 2009; Kim et. al., 2012; De George et. al., 2013; Choi & Yoon, 2014).
This result is consistent with (Fields et al., 2004). On the whole, higher audit fees in the
banking sector can be attributed to the new accounting standard, size of banks and level of risk
(liquidity and profitability risk).
• The Size of Audit firm.
The GradeA variable showed a positive coefficient albeit insignificantly, it shows that client banks of
GradeA Auditors tend to pay more than the client banks of non-GradeA auditors. The interaction
variable IFRSGradeA showed a negative coefficient meaning that in the post-adoption period, Non-
GradeA auditors tend to charge more for their audit service than the Grade-A auditors. This
observation provide primary evidence in support of investment in quality assumption which
assumes that GradeA always has higher quality controls than the non-GradeA companies. This
71
result is consistent with (Lin & Yen, 2016; Lyubimov 2013) generally banks audited by the Non-
GradeA audit firm experience greater IFRS audit fee increases than those audited by the GradeA audit
firms post IFRS adoption.
5.3 Conclusion
In summary, the findings show that preparing financial statements in accordance with the
requirements of IFRS as a rather more complex standard relative to previous domestic GAAPs
increases audit fees.
5.4 Recommendation
5.4.1 Contribution of the Study
The main contribution of this study is that it is one of the few studies to examine the impact of
material changes in accounting rules, such as the application of IFRS, on audit activity from
the perspective of developing countries. The results provide empirical evidence that can be
used to assess the impact of the application of IFRS.
5.4.2 Future Research Considerations
In this study the impact of IFRS on audit fees is only measured with one year IFRS adoption
period, which couldn’t explain the increases in fee will be continuous. Future studies should
consider subsequent years to proof whether the impact of IFRS in audit fees is continuous or
will it be declined later. And also this study is limited to banking industry only further studies
could broaden the scope and could make industry comparisons to better understand the audit
fee formulation and the effects of IFRS.
72
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APPENDIXES
Appendix-A
List of all Grades ‘A’ private audit firms exist in Ethiopia
S. No. Grades ‘A’ audit firms
1 A.A. Bromhead and Co.
Audit Firm: A.A. Bromhead and Co. Auditor: Mr. A.A. Bromhead
2 A.W. Thomas and Co.
Audit Firm: A.W. Thomas and Co.
Auditor: Mr. A.W. Thomas, Ato Melaku Abeje
3 Asrat Gezahegn and Berbersa Audit Partnership
Audit Firm: Asrat Gezahegn and Berbersa Audit Partnership
Auditor: Ato Asrat Bekele, Ato Gezahegn Worku, Ato Berbersa Demisse,Ato Sefa
Abdella
4 Getachew Kasaye and Co.
Audit Firm: Getachew Kasaye and Co. Auditor: Ato Getachew Kasaye
5 Girma Tesfaye and Fasil Audit partner partnership
Audit Firm: Girma Tesfaye and Fasil Audit partner partnership
Auditor: Ato Girma Tesfaye,Ato Fasil Hailu
6 H.S.T and Company
Audit Firm: H.S.T and Company
Auditor: Ato Solomon Gizaw, Ato Tekeste Gebru
7 Kokeb Moges and Melkamu Belete Audit General Partenership
Audit Firm: Kokeb Moges and Melkamu Belete Audit General
Partenership
Auditor: Ato Kokeb Moges, Ato Melkamu Belete
8 T.M.S Plus
Audit Firm: T.M.S Plus
Auditor: Ato Tafese Fremnatos
9 TAY and Co.
Audit Firm: TAY and Co.
Auditor: Ato Alemayehu Kasa, Ato Yeheyes Bekele, Ato Tesfa Tadesse
10 Zemedhun & Company
Audit Firm: Zemedhun & Company
Auditor: Ato Zemedhun Adane
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Appendix-B Selected Banks and their official websites
BNK_NAME bnk_id Financial Years Official Website
Abay Bank S.C. 1 2014-2018 http://www.abaybank.com.et/
Addis International Bank 2 2014-2018 http://www.addisbanksc.com/
Awash International Bank 3 2014-2018 http://www.awashbank.com/
Bank of Abyssinia 4 2014-2018 http://www.bankofabyssinia.com/
Berhan International Bank 5 2014-2018 http://berhanbanksc.com/
Bunna International Bank 6 2014-2018 http://www.bunnabanksc.com/
Cooperative Bank of Oromia(s.c.) 8 2014-2018 http://www.coopbankoromia.com.e
Dashen Bank 9 2014-2018 http://www.dashenbanksc.com
Debub Global Bank 10 2014-2018 http://www.debubglobalbank.com/
Lion International Bank 11 2014-2018 http://www.enatbanksc.com/
Nib International Bank 12 2014-2018 http://www.anbesabank.com/
Oromia International Bank 13 2014-2018 http://www.nibbanket.com/index.php
United Bank 14 2014-2018 http://www.orointbank.com/
Wegagen Bank 15 2014-2018 http://www.unitedbank.com.et/
Zemen Bank 16 2014-2018 http://www.wegagenbanksc.com/
Enat Bank 17 2014-2018 http://www.zemenbank.com/
85
rho .73480729 (fraction of variance due to u_i)
sigma_e .21167395
sigma_u .35234925
_cons 3.311803 1.96758 1.68 0.092 -.5445841 7.168189
big4 .1237527 .1061823 1.17 0.244 -.0843609 .3318662
lev 3.657552 1.068981 3.42 0.001 1.562389 5.752716
roa -1.046644 4.033068 -0.26 0.795 -8.951312 6.858024
liq -.9956568 .768306 -1.30 0.195 -2.501509 .5101953
cr -.2586987 .1144504 -2.26 0.024 -.4830174 -.0343801
rec -.9666467 .7114912 -1.36 0.174 -2.361144 .4278503
size .2916302 .0826645 3.53 0.000 .1296107 .4536497
ifrs .2159568 .0637336 3.39 0.001 .0910413 .3408723
af Coef. Std. Err. z P>|z| [95% Conf. Interval]
Robust
(Std. Err. adjusted for 16 clusters in bnk_id)
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
Wald chi2(8) = 525.66
overall = 0.6610 max = 5
between = 0.6697 avg = 5.0
R-sq: within = 0.6573 Obs per group: min = 5
Group variable: bnk_id Number of groups = 16
Random-effects GLS regression Number of obs = 80
. xtreg af ifrs size rec cr liq roa lev big4, re ro
86
rho .72234934 (fraction of variance due to u_i)
sigma_e .2212282
sigma_u .3568328
_cons 1.89155 2.184899 0.87 0.387 -2.390774 6.173873
iifrXbig_1_1 -.185591 .127822 -1.45 0.147 -.4361176 .0649356
big4 .1458492 .1114184 1.31 0.191 -.0725269 .3642252
roa -1.403547 4.558578 -0.31 0.758 -10.3382 7.531101
lev 2.436542 1.365915 1.78 0.074 -.2406026 5.113688
liq -.8986839 .733224 -1.23 0.220 -2.335777 .5384088
rec -1.578611 .6079189 -2.60 0.009 -2.770111 -.3871124
size .3969317 .0738222 5.38 0.000 .2522429 .5416206
ifrs .2909487 .0648377 4.49 0.000 .1638692 .4180282
af Coef. Std. Err. z P>|z| [95% Conf. Interval]
Robust
(Std. Err. adjusted for 16 clusters in bnk_id)
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
Wald chi2(8) = 896.45
overall = 0.6961 max = 5
between = 0.7238 avg = 5.0
R-sq: within = 0.6321 Obs per group: min = 5
Group variable: bnk_id Number of groups = 16
Random-effects GLS regression Number of obs = 80
. xtreg af ifrs size rec liq lev roa big4 iifrXbig_1_1 , re ro
Mean VIF 1.76
big4 1.13 0.882569
liq 1.15 0.868175
roa 1.22 0.817093
ifrs 1.24 0.809341
rec 2.18 0.458897
lev 2.32 0.430464
cr 2.42 0.413442
size 2.43 0.411739
Variable VIF 1/VIF
. vif
